﻿<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>Millisecond Forums » Millisecond Forums » Inquisit 6  » Is it possible to refactor this test using 1 trial with item lists?</title><generator>InstantForum 2017-1 Final</generator><description>Millisecond Forums</description><link>https://forums.millisecond.com/</link><webMaster>Millisecond Forums</webMaster><lastBuildDate>Fri, 18 Sep 2026 05:09:55 GMT</lastBuildDate><ttl>20</ttl><item><title>Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35269.aspx</link><description>Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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NX2/nrVfV3d2Yi9USg8K/ZUVEiz03tmNg40K/HgwYNQKpWwWCx9VosGIGYoTpo0aUDnICIiIrqYcc3ES9ChQ4fQ3t4OvV4PjUYDAOjo6IDD4UBqaioSEhIk++/cudMrK8BkMiE3N1dSqdFiseDw4cPQ66WBjfb2dlx55ZXn6GqIfNOoNchJz8G2vdsgCAJO1ZxCe0c7QoK9M1xaja04eOIgAE/RjqnjporP5aTnICYiBvXN9ThZdRLlp8oxNmOsz3MeLTmKDnMHAE9m24TsCefgyoB31r4jPlar1EhJSPG5X8/CLIYgA0bEjRj0ua+achW2FmwV25t2bsI9P7zHr2OvnnY15s+ejw//8yEAoM3YhuW/X45P//4pUkf0Xq21P3VNdZJp7Omp6YgOH/rp5UQXC4vFIgbLTpw4gbFjx3r9b+5Jo9FgxIjBvz4Mtf379yM4OBidnZ297tNXIFAmk0Gn04kFXXpSKBRisHL06NHYv38/3G43dDodbDYbTCYT0tPTER3t/VpiNBoREhKCwMBAKBQK2Gw27N+/H0qlEjqdDna7HZ2dnRg9ejRiYs4uG5yIiIjoYsbMxEtEd9XBjRs3wmq1QqPRwOl0wmQywWQyQS6XQ61W4/Tp09ixYwdstu+rtNrtdnG/7i+n0+k13dPpdMJqtXrt62utIqJzTaPSIGd0jtiubaztdY2+QycOobXdk+WSnJCMmMjvP/yplCrcesOtAACny4lvtn/T6zk37dokPg4ICMD4rPGDuoYz2R12fPCfD7ClYIu4LVgf3GvxlYPHD4qPQ4JDkBSXNOgxTJ8wXdLuOZb+aFQa/P2JvyMuKk7cdrr2NJY9tmxQlU5b2lsklbazRmaJN0qILkfdNwVlMhkCAgJQWFiIdevWoaSkBDabDVarFXa73WeQbbjZ7XZYrVbs3r0bwcHBEATBZ4Zid4XlsWN939wBPK/DqameGxVnZhCeOHECcrkcJpMJu3btgtPphNvthslkgsPhgFqtRkVFBfbs2eP1+tRdqTouLg61tbXYunUrAgICxOPtdjvUajVOnTrl83giIiKiSx2DiZcAt9uNo0ePoq2trd+pPAEBAVAqldi5cyeMRs/0yNmzZ0uCi4Dnjn5BQYFkW1FRkdcHeJvNhokTfQc6iM4lpVKJrJFZ4vqCdU11qG+u99rP5XahsKgQHSZPRmF2WrZXVtst198iPu7OqvNl295t4uPYyNhBZdv11NDSgP1H9+OF/3sBT/z1CclzS+Yt6XUtv7aONvGxUqFEoK7vatb+OHPadlV91YD7WPnYSnE9Q7fgxomTJ5B/KP+sx9Rl6ZKslxgRFgFlgPKs+yM6V7q6utDQ0CD5OhcMBoOYEedyuaBSqRAVFYW2tjYUFBRg27Zt2L9/PyorK1FRUQGTydRPj573EmeO3ddXS0tLn/0YjcY+jy8sLMSuXbvEQKfL5fI5/VqpHNjfeM+ZFADEcer1emi1Wuh0OkRHRyM6OhrBwcGw2WyQyWSw2+0oKiqSBF67Z2vU1dWhsbERer0ebrcb4eHhiI6ORlBQkPi+yW6349ixY3C73QMaLxEREdHFjNOcLwFFRUXo7OyUvPE2m82Ii4tDbGwsqqqq0NnZKd5pBwCdTofGxkYYDAYA8Ouuemtrq1jJsJvT6fTaRnS+pCWlISYiBqdqT8FkNqGiqgLCNEFSZMBkNuFY2TE4nA6olCpkj8qGTitdTD87LRujkkah9FQp6prqcPD4QeRm5kr2OXOq7a3zbu13fP/97H/7VW3Y2GlES3sLaptqJRnBP7zhh3j0J4/2elx90/fBU41ag5Ag7yneAzUiRjoVsuc5/DVz0kzcdsNtePtfb4uvLa+8/wqmjpsKRcDA/+2YukzoNH0/DTIiJEJcJ43oQtLe3o6qKmkA3tc02qGQmpqK8PBw1NbW4tSpU2JmnlqtFgNrdXV1cDqdaG5uxogRI/qckut2u1FZ2f8aqTqdDuHh4b0+39jY2G8f3QVhjEYjsrKyxPciQ6n7NcJsNiMnJ0cMKgKeAGBkZCSOHTsGjUaDjo4ONDY2ij8rhUIBu90Ol8uFrq4uTJgwATKZDMHBwQgICIDdbkdUVBT27NmD8PBwtLe3o6GhgUVYiIiI6LLBT2MXObfbjdraWskbcZvNhpEjRyIpyTPl0WAwYMuWLZJqhDKZDA0NDQgLC0N4eDiys7NRVlaGgIAAcR+9Xo+DBw8iNzcXtbW1XkFDl8vV5/QjonMtJSEF0RHROFV7Cm7BjcLjhXC5XZKAVUt7i1iBOSgwyOeUYZlMhqm5U1F6qhSAZ2rvmcHEXQd2Saoq33jNjf2Or+BQQb/7+KJSqnDTdTfhT4/+aVAVi4eLRq3BnTfdiby9eSipLAEAbNq9Ca9/9DoevOPBAVeUFQQBbmHgWT8//c1P8eWWL/3ef9lNy7Dy8ZUDPg9RN5lMJrlxd64ZDAYYDAZkZmbC4XCgoKAA7e3tMBgMUKlU4hInbrcbZWVlaGlpQXZ2dq/9+TP2/v5+ZTKZ1z49s/ZcLhdaW1uRkJCA66+/vt/zna05c+b0+pxKpUJERARmzpyJDRs2IDQ0FPn5+Vi0aJFkP7vdjmnTpnmtR9l9/Pz587F+/XqEhITg0KFDDCYSERHRZYPBxIvcvn37vO7oh4SEIDIyUrItOzvbq9Khw+EQs4YEQfC5tlL31KiKigqvTCCn08l1gmhYhRpCMSpplFgxuKi8yPOh9fuYOKrqq3C69jQAIDwkHOmp6T77mj5+Oj758hM4XU7s2L8DDyx9QJxCDUiLncRFxSEjNWNIryVYH4zo8GgkxSXh1htuxbxZ8/zKarxQZY7MxM+X/hz/8/z/wOH0ZFuufGslJo2ZhCvGXzHMoyM6N2JjY4ctoKRUKjFjxgwAnv/pJ0+ehNFohMvlgtVqhUqlQlNTE5qbmxER4V2FXqFQDMmyJWlpaV43H48ePYqOjg4EBATA4XAgJyen34IwTqdzQBnIZ/N+RCaTIT4+Hl1dXT7XbdRoNP0GWGNiYmC1Ws9rEJmIiIhouDGYeJFzOp2SbELA84a6tra232PVarU4NTosLAx6vR5Wq1Wyj0qlQktLi9ebZEEQEBQU5LXgOdH5NjV3Kj5c51nnsLSyFE2tTYiPjhef37BjgxjMmjx2cq9TgUcmjkRsVCyq6qpQ01CDiuoKMWDYZe3CgaID4r5X5PoXDPv9L36PmAjvaYUV1RX414Z/iVl7gCfT8cc3/hgZKRkI0gf51X+wPlhcC9LpdMJitUCr8f5APBANzdI13np+Lwdqydwl2HNoDz7+6mMAnu/j31b9DakjUhEd4f/UT61Gi0BtIMwWMwCgvbMdLpfL67WP6HJgtVpRXV0NwBO480Umk2HkyJEAgLa2NjQ0NKCxsRFarRbFxcU+g4nnUkZGBoqLi9HZ2QmNRoPq6mqEhob2uc6zyWRCSEgIqqqqer1Ot9uNpiZPcabudaAHojuYWFpaKrkx29HRAY1Gg+jo6H6LPSUmJqKkpOScTNUmIiIiulAxmHiRCwkJQWdnp2Sb3W7vd4F0wFOMpTtIqFQq4XK5IAjS9ebsdjsOHDggVlXs1p3FqFKpBnsJRIMybdw08bHNbsOBYwckAbCe1YgXXSudwtZTXFQckuKSUFVXhYbmBhwrPSYGE+sa68Rq0AAwLXdab91IXDf9OoxOHu213e12Y/mPl+OXz/0Sq79ZDQBYu34tFAEK/OHhP/jVNwDER8WLwUSLzYLWjlbEa84++Ad41oaUnGMQwUSNWoNnf/UsDpccFqea79y/E1v3bMVt82/zux+dRgedVicGE9uMbXC6vG+knOkff/hHn0URSk+V4pq7rvF7HEQXAovFgtraWqjVajgcDp/FS3oKDQ1FSEgI1Gq1ZK3k80mhUCArKwvfffcd9Ho9FAoFdu7ciRtuuKHXY7ozDfsKEgqCALPZ87pw5s3QwbBYLNBoNFAqlcw4JCIiIvKB75AucgNde6wvaWlpcDqdkm0KhQJyudzrA7kgCOKajETDKSUhBUlx3/8ufr3ta/Hx8fLjKK30rIMYGhyKq6de3Ws/MRExyByZCZlMBlOXCSerToofZksqS9De2Q7As+5iVlrWoMYsl8uhUWuw4qEVWHz9YshlclhtVqz6fBV+9/ffoaWt/5sBAJA16vtxdJo7UddQ18fe/tl1YJekfc0Vgwu26TQ6rHpuFQK1noILdocdK99aifLT5X73ER0RLQlqnjh5Ahabpd/jVEoVNGpNr189p7ETXSwEQRBfm/wpdgJ4AnN2u118PBxkMhmuvfZauN1uCIKAsLAwbN++XVJ0qqfujMC+KmILgoC2Nk9V++6iLt127NiBgoIC1Nf3XkRKEATU1NQAgJjhCEBcI/H06dPo6urq87q6s0S7x0FERER0OWAw8SJns9m8tul0OiQnJ/v11XONoODgYFgs0g/oMpkMer3eKwPIbDazijNdMG65/hbx8Xe7vxMf9yy+ccOs3jNguk0dNxUqpSfbdseBHegwe7L+KqoqxGrCaUlpiA4fmuqskWGR+M39v0HGyO/XX3zv3+/hL//8CzrNnX0c6TFj4gzxcZuxDSerTg56TAWHpUVjrr9ycAUSZDIZkuKTMOfKOeLNj8qaSvzupd/53UdMZIwkmHis7Bgs1v6DiUSXosDAQEREREAQBKhUKtTV9X8TwWg0ioHHjo6Ocz3EPuXm5oo3KAMCAnDq1Cmf+40cORJutxt6vb7X2RbdU7ddLhdyc6VFs7ozFg8dOtTrWARBEIOVPWdg5OTkwGq1wul0SoKMvjQ3N/f5PBEREdGliMHEi1x3gZQztwmCgOjo6H6/zpymPGvWrF6zBHoaNWrUkF0D0WDddN1N4uNWY6u4FuHXed9nKc6fPb/ffqaNmwalwrOO6OETh9Fl6UKXtQulp0vFSs4jR4xEZHhkX90MSFJcEv792r/FzD0AWLN+jWTsvckcmYm4qDgAgNliRv6hfHRZ+86i6cvx8uM4UnxEMraEmISz7q+nX//XryVVtjft2oS/vvNXv47VaXSYnDNZPL7N2IZvtn0zJOMiutio1WqoVCoIggC5XI7i4mKUlZX1eUxhYaG4RnJKSsr5GGavNBoNwsPD4XA4EBAQgObmZrS3t3vtFxgYCKvVCrVajeLiYp99HTlyBEqlEp2dnV6F55KTkwF4bpTu37/f1+HIy8tDYGAgTCYTpk6dKm43GAxwu91QqVSoqqrqNeD57bffQqvVwmKxYObMmX5dPxEREdGlgMHEi1xERITPNcFqa2vR0tICs9ksqdhsNpvR3t6O4uJibNmyxWstIrVaLd7N701ra6v4Jp3oQpCWlCYJehUcLMCx0mOobvBMP4uOiMboFO+1C88UHREtrodo6jJh065N6DR1oqTCE5xUKpRIT00f8irLocGh+PMv/ywWT+k0d+LVD19FcYXvD9DdEmMTJVOuN+3ehFM1vj/09sflciFvTx6a2jxZODKZDMtuXnZWffkyOmU0Vj62UqzOKggC3v/ifRQWFfp1/PUzrodepxfbK99aiTYjpxXShcXhcMBsNnt99baen8vl8rm/r6+ey5Ckp6dDLpfD4XBAq9WipaUFX3/9NQoLC9Ha2gqz2Yy6ujps3rwZ27ZtQ1BQENxuN+x2OxIShuYGwdmSyWRIT0+HTud5HRUEwWe2ZHBwMCIjI8WgaV5eHhobG2E2m3Hy5Els27YNISEhEAQBaWlpXsu+xMTEwG63QyaTwWazYceOHeL35tSpU1i/fj10Oh1kMhni4uKgVkuXPZg8eTLsdjsUCgUqKyuxc+dO8X1VVVUVNm7cKBah0+v1/RZqISIiIrqUsADLRS4jIwObN28W1/cBIH7AOHjwIIKCghAeHg6VSgWXy4XGxkaYTCYEBgaKb+TPlJKSgubmZp/FDdxuN1JTU8/Z9RCdDblcjglZE1Bd7wke5h/Kh1twi1Nhx6aP7bWK85kWXbsIm3ZtAgCs27IO08dPx4mTJwB4CorkjM45B/NIwJwAACAASURBVFcAzJ81H9v2bsPnGz+H2+3G8fLjePGdF/HmH97s9ZjIsEgsunYRtu/bDpvdhrrGOjz7j2fx3vPvDfj8NQ01+PjLj2G1eYIeibGJmHPlnLO+Hl+W3rgUG3dtFKef1zbUor6p9/XMehqVNApLFy7Fax++BgBoam3CX978C363/HcI1AX2czTR+dHU1ISqqiqv7WFhYT4z+q1WK44ePepX36mpqZLsu6lTp+LYsWNoaWmBSqVCeHg47HY7SktLxX263xvYbDYYDAZkZ2cP9JLOmejoaBQXFyMwMBAVFRXQarWS61OpVIiKikJzczO0Wi00Gg0qKirE59VqtVg0LiYmxqt/g8GArKwsHD16FBqNBgEBAZLvTUhICJxOJ3Q6HRITE72CkXq9HtnZ2eLxACQZoMHBwXA6nVAqlRg9ejSryxMREdFlhZmJl4CJEyf6vKuv1+shCAKam5tRW1uLhoYGCILgtUj5mUJDQ32uxQh4PvhEREQMybiJhkqAPAATsieI7ZLKEuTtyYPd4Sk4MC59HAxB/lUwXXjtQjHzMP9gPgoOF4gVk7UaLcaMGjPEo/cICQ7B/bffLwl6rvtuHT779rM+j1t07SJJgHP9jvV48u9PDvj8jz77KI6fPA7As47ZwmsXYmTiyAH305+H7nxI7NctuMXp4/749X/9GmlJaWL7k68/wT9X/xM2u+/Xq740tTbhyb8N/PtEdCHJzMzEhAkToFar0dTUJFn6xG63o7m5GQ6HAxMmTEB2draYGXwhiI+PR1xcHJxOJzQajc+1DaOiojBp0iQEBQWhpaVFnGlhs9nQ3NyM6OhojBs3rtf3NeHh4Zg4cSIEQUBLSwucTicEQYDJZEJ7eztyc3ORlZXV6/FhYWGYOHEiDAaDeHz3+buPHzt2LIKDg4fou0JERER0cbhw3lXSWQsJCUFOTg4qKirgdrv9/rDgcrkgCILX9u6pRb6mO+t0Oq+pQETDTSaTISM1A8H6YHSYOlBaWYrKmkoIgoDQ4FCMzRgLudy/eyc6jQ5Txk7B1j1bYbPb8NKql8TnMlIzEB0xNMVXfMnNzMWym5fhpVUveQJtTieefvlpjM8cLwmi9aTVaPHq06/i5uU3o7axFm63G++sfQdymRwP3vEgosKjej2fy+VC+elyPPLnR7D3yF5xe0ZqBu5efLe4fuRQmpA1AUtvXIrn/vEcHM7+12ftSa/T49WnXsXSXy5FS3sLzBYzVr69Ela7FT9d/FOEGcL6HXN7Rzu27d2GFf+7AlX132eQyWVySUEqorMRFxeHuLi4fvdLSkpCUlJSv/v1Ry6XQ6/XY/z48Rg/fvxZ9REbG4vY2NhBj6XnmoP+ysjI6HcfvV6PrKwsZGVl9btvb8dPmzbtrI4FPGs3ZmRk+DVWIiIiossFMxMvETExMcjKyoLBYIBSqURXV5dXMFAQBHR1dcFisUCj0SAsLMxn4LHn4u49uVwuBAUFSaZUE10okuKSkBTn+XButpjR3uFZ0D/UEIqMlIF9CLzmimvEx5U1leLjRdctGoKR9u2J+5/AVVOvEtutxla89tFrfVZ3Th2Rij89+ickxiUCAOwOO/65+p948JkH8fFXH+Nw8WFJ9l6bsQ27CnfhtY9ew91P3I19R/eJz40ZNQavPf3akBVe8eXHN/5YXJtyoMaMHoOnlj+FMIOnmrzNbsOLb7+IJQ8twd/e+Rs27d6E2sZaWGzfV3uua6xD/qF8vPuvd3HfU/dh+R+WSwKJgdpA/HD+D3HHwjsGd2FERERERESXAWYmXkIMBgMMBoMYMAQgqdYsCAIcDgdkMhm0Wm2vWTgdHR0wGo1e6wcpFAoYDP5NFSU63xLjEpEUl4QjJUck25Pik8Qgm78mZE2AIcgAY6e0QNGia859MBEAfnPfb1BSWYLq+mq4XC58ufVLLLhqgSTIeaa5M+dCpVTh8ZWPo6q+Ck6XE1vytyD/YD6iw6MRERoh3jywWC1obG1Ec1uzWL1dLpdj1qRZeOrBpyRFXc6F8JBwvPTkS7juJ9ehtb11QMeqlCosmbcE2aOy8fOnf47SU5410E6cPIHSU6UIDQ5FVHgUtBqtmKXYaepEe2c7GlsavbIhRyWPwlPLn8KVE65EUGDQ0FwgERERERHRJYzBxEuQTqfrtbiKP6xWK7q6urwqE5rNZsTHxw92eETnhEqpwuiU0ZDnyeEWvq9wPmf6nAEvjB8TGYOUhBQcPH5Q3Jaeku73uouDlZuZi5/98Gf442t/hMPpQJuxDSteWYErJ14Jtcr3MgNKhRLXz7geY9PHYvnvl2PPkT2w2W2wWC2orKmUZFj2JJfLodPocNv82/DE/U8gWH9+1v4aETMC//3T/8ZTLz3lsyJ9X1RKFcZljMM3//cNnv3Hs/jXhn+h09wJp8uJ5rZmNLc193m8UqGERq3Bfbffh/tvv/+8/VyJiIiIiIguBQwmkpeKigqvQCLgWZuR6EJ23fTr0NjSKAkmXj3t6gH3ExUWhaULlkoy9CZmT+z3uMljJ8Ph+j7zzaA/+yDVomsXobGlEW0dbeK2vUf2YsbEGX0eFxMZg4//9jG2FGzBV1u+womTJ1DXVIeW9hYxK8+gNyAsJAyxUbHIzcjFrTfcOuDCMkvmLUGXtWvgF9bDLXNuQXNrMxpbG8VtkWGRfRwhZQgy4LlfPYc7Ft2BDds3YN+xfahrrENjSyNaja1icRe1So3wkHCEGcIwKnkUJo2ZhPmz55/TqdxERERERESXKpngqwIHXda2bNnildnY0dGBmTNn+gwy0rlhPGGEwziwAhVEPdnsNtQ21qK5rRnGTqMYXNPr9DAEGRARGoHIsEgoAi7++0qCIKC9ox3Nbc1oNbaiw9QhXq9KqYIhyACD3oD46HjotGefuX05C8kOgUJ/8f+uEBERERHR4PBTAUns2rXL5xRphULBQCLRRUatUiMlIQUpCSnDPZRzTiaTIdQQilBD6HAPhYiIiIiI6JLGas4kstvtMJlMXtudTiemTJkyDCMiIiIiIiIiIqILCTMTSSQIAiZMmIAzZ747HA5JVWgiIiIiIiIiIro8MZhIIrVaDbXad6VYIiIiIiIiIiIiTnMmIiIiIiIiIiIivzCYSERERERERERERH5hMJGIiIiIiIiIiIj8wmAiERERERERERER+YXBRCIiIiIiIiIiIvILg4lERERERERERETkFwYTiYiIiIiIiIiIyC8MJhIREREREREREZFfGEwkIiIiIiIiIiIivzCYSERERERERERERH5hMJGIiIiIiIiIiIj8wmAiERERERERERER+YXBRCIiIiIiIiIiIvKLYrgHQES+KQOVkMlkwz0MIiIAgCyAr0dERERERATIBEEQhnsQREREREREREREdOHjNGciIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/KIY7gH0RxAECIIw3MMgIho0ufzyuX/jdruHewhERIN2Ob1uExEREfnrgg8mtrS0oLy8fLiHQUQ0aFOnTh3uIZwXdrsdhYWFwz0MIqJBy8nJgU6nG+5hEBEREV1QeLuViIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8wmEhERERERERERER+YTCRiIiIiIiIiIiI/MJgIhEREREREREREfmFwUQiIiIiIiIiIiLyC4OJRERERERERERE5BcGE4mIiIiIiIiIiMgvDCYSERERERERERGRXxhMJCIiIiIiIiIiIr8ohnsAF5O8vDxJOykpCcnJycM0GiIiGoyuri7s3bt3wMclJycjKSnpHIyIiIiIiIjowsdg4gA89thjkvbdd9+Ne++9d5hGQ0REg9HY2Oj1uu6Pe++9F3ffffc5GBEREREREdGFj9OciYiIiIiIiIiIyC8MJhIREREREREREZFfOM2ZiIguS2FhYXj44Ycl27744gtUVlZKtp25z9ixY8/52IiIiIiIiC5UDCYOwNq1ayXtoKCgYRoJERENVnBwMH70ox9Jtu3Zs8crmHjmPkRERERERJczBhMHID4+friHQERERERERERENGy4ZiIRERERERERERH5hcFEIiIiIiIiIiIi8gunOQ9AY2OjpB0YGIjAwMBhGg1d6NxuN9rb27Fv3z58++23OHz4MEwmEwAgMzMTEydOxHXXXYeUlBSo1Wqv4zs7O2GxWMS2Xq+HTqfz69xmsxlms1lsBwcHQ6PRDPKKiIaf2WxGdXU1tmzZgoKCAlRVVcFkMkEmkyE2NhZjxozBtGnTcOWVV0Kv1yMgIGC4h0y9MJvNOH36NL766iscPHgQZWVl4nO5ubkYO3Ys5s+fj6ioqF5f++x2O9rb28W2P/+XbTYbjEaj2Pb12trz/31UVBTsdju+++47vP/++ygvL0dwcDDGjx+PH//4x0hMTITD4YAgCAAAnU4HvV7v1/fAZDKhq6ur3/HbbDbU1NTg22+/xe7du1FZWQmHwwG1Wo0pU6Zg5syZmDlzJoKDg33+zre0tMDlcgEAAgICEBwcDKVS2e/4XC4XWltbxWvr/n4QERER0eVNJvR8h3gBam5uRnl5+XAPAwAwbdo0Sfvuu+/GvffeO0yjoQtZR0cHtm7dilWrVqGmpqbX/fR6Pa655hrcdtttGDlypOS5VatW4fXXXxfb8+fPx1NPPdXvuR0OB/7617/i888/BwBoNBqsWLECV1111VleDQ2VqVOnDvcQzgu73Y7CwsIh7bOrqwsFBQVYt24d9u/fD5vN1uu+MpkMI0eOxE033YTFixdDJpP5fZ5HH30Uu3fvlmzLz88/63GTb8XFxXjzzTexZ88eOByOXvdTqVSYMWMG7rrrLmRkZHg9X1BQIKm2ff/99+MnP/lJn+fOy8vDY489JrYfeeQR3H777ZJ9ev6/37lzJ9544w2sXr3a6/fOYDBgypQp2LVrl3gDZ/bs2fjLX/7S5xi6PfHEE/juu+/Ea3344YexePFiyT6nTp3C6tWr8e2330puEp0pISEBt99+O+bNm+cVzHzggQdw4MABAEBISAiefPJJzJgxo9/xFRUVYfny5eKNrejoaHzxxRd+XdulIicnx+8beURERESXC05zJhpiNpsNH330EV566aU+A4mAJyvlP//5D/74xz/i0KFDkucWLlwoaW/evBktLS39nt9qtWL79u1iOz4+HomJiQO4AqILi9FoxFtvvYU///nP2LVrV5+BRAAQBAFlZWV49dVX8fzzz5+nUZK/Tp48iRdffBE7d+7sM5AIeALTW7ZswQsvvIDTp0+fpxFK/fOf//QZSAQ8mYRz585FcHCwuK2goABtbW399tvW1oZdu3aJbb1ej4kTJ0r2KS0txRNPPIHPP/+8z0AiAFRXV+P111/Hm2++6fVcz/8nRqMRhw4d6vd7DwDbtm2TXPfcuXP7PYaIiIiILn0MJhINsc2bN+Pdd98VP/gFBwdj6dKl+OCDD5Cfn4/169fjmWeeQVxcHORyz5/g8ePH8X//939obm4W+wkNDZVkE9psNnzzzTf9nn/btm2SfjIyMpCamjpUl0d0XrndbvzjH//Ahx9+iM7OTnF7QEAAVCoV1Go1NBoNNBoNFAqFJAvRYrHg888/x8qVK+F2u4dj+HQGl8uFr7/+GocPHwbwfRbpn//8Z+Tn5yM/Px/r1q3D0qVLxWwwQRBw7NgxbN26dVjG/O6778JutyMxMRHPP/888vPz8dZbbyExMRGZmZmYMWMGMjMzxf2tViu2bNnSb7/btm2D1WoV28nJyUhOThbbzc3NeOGFF1BeXg632w25XI7ExESsWLEC3377LfLz8/Hxxx9j8eLF4vfKbDZj9erV+OSTTyRTk0eOHImEhAQAnu9nfn5+vwHP5uZmHDlyRPzb0Wq1uPnmm/34jhERERHRpY7BRKIhVFVVhZdeeklsJycn49lnn8UvfvELpKWlAfBMi5szZw7eeecdLFy4UFy3qrCwEJs2bZL0t3TpUsn6V3v37u03O+Xf//63+Fgmk2HmzJmDvi6i4bJmzRp8+eWXYlsmkyE5ORkPPvgg3n77baxfvx5bt27Fxo0b8fzzz2PevHnQarWSPrZs2YLdu3fjAl/V47Jgt9sl08YTExPx9NNP45prrhG3RUZG4oEHHsDy5csl6wee+fp4PiUmJuKPf/wjZs2aBQDIzs7G6tWrsWzZMgDAokWLJPt/8cUXsNvtvfbncDiwbt06ybYf/OAH4mO3242NGzfi+PHjADzLVdx888344IMPMG/ePISEhAAAUlJS8Otf/xovvPCCJBD51ltvobi4WGzHxcVJAp4VFRWoqKjo85pramok+0yYMAFBQUF9HkNERERElwcGE4mG0Pvvvy8u7K9SqbBixQqvaWvdDAYDfvaznyElJQUA4HQ68dlnn0n2yczMxOjRo8X2yZMnceLEiV7PX1JSgiNHjojt0NDQy2adPrr0HD58GK+//rokKDN58mQ888wzuO2225CWliYWFlIqlZg+fTr+53/+Bw8++KCkuERLSws2bNjQZ3CHzg+XyyWZrhwfH++1XiwAKBQKzJ07FykpKUhLS8OCBQtwww03nM+himQyGSZPnuxznN2vz7m5uYiMjBS3V1dX4+TJk732WVFRgerqarEdHBzslYn+xRdfiFORc3JycM8990ClUvnsb+LEiXjsscfEDEWTyYQNGzaIzwcGBmLixIlisS+n04m1a9f2ed0HDhxAa2srAM/PY/LkyVw7kIiIiIgAMJhINGRaW1tx8OBBsX3llVf6LBjQU3h4OG699VaxXVNTgz179ohthUIh+YDZ1NQkmXZ2pjVr1kjaN998s1eWFtHFYs2aNV4VzX/1q19h1KhR4hIBZ9JqtVi4cKFX4OnMKaU0PARBkAR1jUajZFmGnvR6Pd544w28++67eOKJJ7yKpJwvCoUCEyZM6LMyuFqtlvzOWa1Wr0I+PZ2ZZT5t2jRJFmZpaSkqKyvF9rXXXovQ0NA+x5mRkSEWjhEEAUVFRWhqahKfv+KKKyTBwO3bt0uqVp/pq6++Eh9HREQgOzu71787IiIiIrq88F0h0RA5ceKEmJUIeIKJ/hg7dqyk3XMKoEwmw9ixYxERESFuy8vL8znVuampCUVFRWJbp9N5VQUlulgcPXoUR48eFdtyuRy/+MUv/CompFQqMWPGDEngxGKxYMeOHedkrOQ/pVKJnJwcsX3ixAn87W9/w969e1FdXe2VPapQKKBQKCCXywdUlXsoyeVycZmKvsycOVPMHHS5XDh+/Lhknc9uZrMZRUVFYtahQqHAvHnzJPucuT6uPxnmKpVKMtW5sbFREiyMjo7GFVdcIbYFQcBHH33ks69Dhw5JMieTkpIwatSofsdARERERJcHxXAPgOhS0djYKKl6mZeXh2PHjg24n54BFAAYNWoURo0aJWbvlJeXo7i4GJMmTfI6rqGhQWxPmzYNYWFhAz4/0XATBAHFxcWS3+fExERcf/31fvcRHx+PmJgYyVTTHTt2SNalo/NPpVLh+uuvR0lJCWw2G1wuF7Zu3Yo9e/YgOTkZqampyMnJQW5uLpKSkoZ7uAA8wcSeN3R6Ex8fj9GjR4uv4eXl5aitrUV6erpkv4aGBpSUlIjthIQESRAQgLhWYrf33nvPr7H2XOOwvb3dq8jKXXfdha+//lps7969G3fccYfX9b3zzjuS9tVXXy0uKUBERERExGAi0RBpamqSBBO3b99+Vv3U19dL2nq9HuPHj0dBQQHcbjfsdjs+++wzSTDRZrOhsLAQJpNJ3DZnzpyzOj/RcHM4HCgpKYHL5RK3jRkzBgqF//+yQkJCEBwcLNnW0tIyZGOksyOXy3Httddi//79kurMXV1dKCoqwvHjx7FhwwbodDpkZWVh/vz5uO6664ZxxB7+rBUYFBSEsWPHisHE2tpalJeXewUTy8vLUVNTI7bHjRvndeOntLRU0v78888HPOauri7JMgGApyhYTk6OuLZuU1MT9u3bJ8mMPHXqlGS5DQAMwhMRERGRBKc5Ew0RQRCGpFqsrz5mzZolKSiRl5cnmVLd2dmJffv2icempqZeMFk9RAPldDolRToATxBkIOu1hYeHe60xd/jw4SEZHw1OWFgYnnvuOdx3331ISUmBXq8Xn+teU7G9vR27du3Ck08+iSVLluCbb77xCoxdaJRKJbKyssTrEQTBa7oyAOzcuVNc91aj0SAzM9Mr669nIH0wfP0/WbBggThlvKurC4cOHRKnXAOe6uc91+VdvHix5P8PEREREREzE4nOkZtuugmxsbEDPs5XBkxycjImTJggWdD/o48+ws9//nMAQFFREU6dOgXAs85iRkbGWZ2b6ELgcrlQW1sr2Xbw4EGf68/1pa9qujT8fvrTn2L+/Pk4fPgwjh07hsLCQlRUVHitm1hdXY0XXngBJSUlePjhh4dptP7Jzs5GZGSkmCV+9OhRtLS0IDw8HIDnxs/OnTvF/UNCQjBmzJh+++1+rR8oX+scjh8/HjExMairqwMA7N+/HzU1NUhOTobRaMSBAwfEfbVaLW688cazOjcRERERXboYTCQaIkqlEnK5XMzoGDdunFdF2cFYtmyZJJiYn5+PpUuXwmAw4KuvvhIzWZRKJSZOnMgqznTRcrlcXhV+d+zYwQIql6Do6GjMmTMHs2fPhtFoRE1NDfbt24evv/5aElDu6urCmjVrMGHCBMycOXMYR9y36OhopKWliWsXWiwWfPHFF7j77rsBeH6PewbFk5KSkJKS4tWPTqdDV1eX2L7hhhsQFRU1JGOMiIhAbm6uGEysrq5GcXExkpOTUVFRId6YAoD09HSv9RyJiIiIiDjNmWiIREdHS6aqVVVVDWn/ubm5GDlypNhubGzEsWPHUFVVhby8PHF7UFDQBf1hm8gfQzXNky4OKpUKkZGRyM3NxT333IPVq1fjlVdekWTWORwOfPDBB4M+15mB6qEkl8sxd+5cybZ169bB6XTC7XZj9erVkudmz56NgIAAr36ysrIk7Z5rLA6WTqfD+PHjxRtObrcbGzduhNvtxoEDB8TCR3K5HFdffTXUavWQnZuIiIiILg3MTCQaIgkJCZJskt27d+Pee+/t97jm5mbs3r0b0dHRiIuLQ0JCQq/7/uAHP8DLL78MAOjo6EBxcbFkShrg+XB6ZuEJoovd9OnTfWZw0cWls7MTjY2NqK2tRX19PW699Vaf+ykUCkyaNAlPPfUU7rzzTnH7mVWOz2SxWOByuXwG6LqduR7nUBs/fjxCQkLQ3t4OwFO9+ejRo1CpVJKp9zqdDtdcc43PPiZNmoR9+/aJ7b1792L8+PF9ntftduPo0aNoampCVFQUEhMTYTAYfO47ZcoUhIWFiUHKwsJCNDQ0SLLfIyMjkZ6eLq6vSERERETUjcFEoiGSnp6OqKgoMeuluLgYeXl5mD17dp/Hffzxx1izZg30ej2CgoIwf/583HXXXT73HTduHCIiItDc3AyXy4W8vDw0NjZK9rnnnnuG5oKILiBz5swZ0mUDaHg8/fTTqKqqQkdHB0wmE3JycpCRkdHr/meu+XfmmrJKpRIajQZWqxWA5+aMzWbrtfqyIAjYtWvXIK+ib4GBgZg7dy4+/fRT8Zw7d+6EUqmUFDqZOnUqQkJCfPYxd+5cvP322+L6kfn5+ViwYAHi4uJ6PW9XVxdeeeUVnDx5EoGBgUhOTsaDDz7oc93EmJgY5ObmisFEs9mMN954QxKsTUlJ6fNnQ0RERESXL05zJhoiarUas2bNErM43G43Vq5cicrKSp8VNQVBwMGDB/HVV1/BZrOhpaUFp0+fRnZ2dq/niI+PR3p6utg+ceIEWltbxfbkyZMRFhY2hFdFdP4pFAokJiZKttXV1UkqzNLFKSwsDFVVVTAajXC5XPjss8/gdDp97isIAjZv3izZNm3aNElbq9VKMrH379+PpqYmn/05HA6sWrVqyJeg8GX+/Pli9XFBEFBQUID8/Hzxd1gmk+GWW27p9fiwsDCMGzdObJeUlGDdunWw2Ww+93c6nVi7di0OHz4Mk8mEhoYGOJ1Or4rmPS1cuFCSdbh+/XrJz2LKlCleVaaJiIiIiAAGE4mG1OLFi5Gbmyu2m5qa8PTTT2Pz5s2or68Xtzc0NGDr1q14+eWXYTQaxe2zZ8/GxIkTe+0/JCQEubm5UCi8k4rlcjnmzZs3RFdCNHxkMhn0er1kW01NDYOJl4AlS5ZIfrbbt2/HSPxbuAAAIABJREFUO++8g9LSUpjNZnF7fX09Nm3ahNdff13cFhgYiCVLlkj6i4yMRFJSkuS41157DYWFhWJ/JpMJx48fxxtvvIE33njjvKwBmJCQILnxU1FRgbKyMsnzPdfAPZNKpcKSJUvEm0NOpxMffPABXnnlFRw7dky8NqfTibKyMrzzzjt4++23xeMDAgIwd+5cRERE9HqOcePGIS0tzedzSqUSV111lX8XS0RERESXHU5zJhpCQUFBeOSRR/Dkk0+K2S/FxcV44YUXEBcXJ34wbGtrQ11dHdra2sRjs7Oz/ZqiPH36dLz//vvo6OiQbI+JiUFmZuYQXg3R8FAqlRg5ciSKiorEbYcOHYLD4fAZSKeLR1paGhYuXIhPP/0ULpcLHR0deO+997B582aEh4eLmXCtra2ora0VX+cUCgUWL16MMWPGSPoLCwvD7NmzcejQIXFKcF5e3v+zd+fxUdX3/sffk9myAQmBJBAgYQthCSD7LiioCG4tCgW11rpQtdq63ltbW6/XtfWqrVqtda1LFesCFUGsgkAgkLDv+5IAIYGE7Jn190d+c5jJelgT4PV8PHiQc+ac7/meyWR7z+f7/Wrz5s3q2LGjMQT68OHDOnTokCIjI3XllVfq008/PaP36XQ6NXjwYGPYcPDwZkkaOHCgoqKi6j3fYrFo6NChmjRpkt5//335/X653W7NmjVLGRkZSkxMVHh4uLxerw4dOqTc3NyQa0ybNk3jx49vtJ9TpkzR008/XWv/oEGDGhxSDQAAgAsbf5UBp1mPHj305JNP6tFHH1VOTo78fr+OHTsWUoEYzGKxKD4+Xo888kiDlSoBXbt2Vc+ePZWZmRmyv3///mrXrt1puQegKTkcDqWnp2vOnDnGvpycHK1atUojR45swp7hVNlsNt1yyy3KycnR4sWLjZBsz5492rNnT53nBKqub7nlljofmzJlipYsWaLMzExjSonDhw/Xmk82MjJSjz/+uHw+3xkPE202m3r16qWoqKiQikupOmjs27dvoxWS4eHhuvvuuxUfH68XXnjBqMzNzc2td3Vni8Wi6dOn65e//KWpfg4fPlxt27atNTT8rrvuMnU+AAAALkyEicAZkJqaqtdee02zZs1Sdna2Dh06pMLCQmM+qvDwcLVo0UJJSUlKT0/XjTfeWO+qm3W58cYbQ8LE8PBw9e3bVxEREaf9XoCm0KNHD3Xs2DFkfru//OUv6tq1qxITE0+oLY/Ho927d6tz585UNjYDLVu21HPPPadPP/1U3333nfLy8lReXh5Sqd2yZUu1bNlSycnJGjdunCZPntxgmy+++KL+9a9/af78+Tpw4ICKiork8XjkcDjUpk0bdevWTVOnTtXAgQO1aNGiM32LkqoXj+nQoYO2bt0asj8+Pr7e4cV1uf7669W9e3d9/vnn2r59u/Lz81VWViafzyeLxaKoqCi1adNGHTt21BVXXKExY8aYbrtly5YaPny4Zs+eHdLvuhZtAQAAAAL4qwo4Q+Li4nTnnXcqPz9fubm5KigoCAkTW7VqpU6dOikuLi5kEnwzai6y0rJlSw0ZMuS09R1oaikpKerXr19ImLhnzx699NJLuu+++04oUPzss8/02Wef6fXXXz+h0B5n1pQpUzR+/Hjl5uaqtLQ0ZDGpVq1aKTY2Vl26dDE9x+F1112nMWPGaN++fTp69Kg8Ho+cTqfi4+PVqVMnY6GWtLQ0/f73vzfOq2t6iODHrVbrSd1fQkKC7rrrrpD7kqrvLSUl5YTa6t+/v9LS0pSbm6u8vDyVlJQYYWJ0dLQSEhLUoUOHE35DyWq11hpubWZ4NAAAAC5shInAGRQYwhwfH39a2/3qq69CtkeMGMEQZ5xXnE6nbr/9di1cuFClpaXG/kWLFunw4cP6r//6r0arpxYuXKiXXnpJ+fn58ng8da6qjqYVExOjmJiY09JWWFiY2rZtq7Zt2zZ4XEJCgiZOnNjgMY09bobNZtPQoUNPuZ2A8PBwde3a1dR0GGaVlpZq3bp1xnZCQkKDi4ABAAAAEmEicM4pKyvTvHnzjO3w8HBNmzbthKsbgeYuISFBTzzxhP7whz8Yc476fD5t3LhRN910k4YNG6aBAweqe/fustvtkqrnk9uyZYuysrK0b9++Btvfs2ePpk2b1mg/hg0bFrJ9xx136NZbbz3JuwKaj9zcXG3cuFFS9Ztf6enpJ1w1CQAAgAsPYSJwjpk/f35Ipda4ceP44w/nrWHDhunee+/Vm2++qQMHDoQ8tnz5ci1fvryJegac+15//XXjY7vdrjFjxig6OroJewQAAIBzQVhTdwBA/Xw+X8iccR9++KHefvttuVwuSVJsbKxmzJjRVN0DzjiLxaIrrrhCTz31lHr06HFSbbRo0ULTp09ngSJc0A4ePCi32y1J2rVrlx555BFlZWUZj6empmrs2LFN1T0AAACcQ6hMPAE15+eKi4trop7gQuH1evXb3/621mqgUvV8XJMmTVLHjh2boGfA2WO1WpWWlqZ3331XX375pb7++msdPHhQ5eXlqqqqMsJ1qbq6yul0qkWLFmrXrp1GjBihq666qs6FVxwOx0mtWsv3fpyLli1bphdffDHk6yWgZcuWevjhh+VwOJqgZwAAADjXECaegH/84x9N3QVcYMLCwtS7d+86w8RLL71UU6ZMMb3SKXA+uOaaa3TFFVdo9+7dOnjwoI4cOaJjx44Zi6u0bNlScXFx6ty5szp06NBgONK+fXu+r+OCkZqaKqfTWStMjI+P18yZM5WamtpEPQMAAMC5hjARaMasVqsuvvhirV27Vrt27ZLdbldqaqp+8pOfaNCgQXVWWwHnO6fTqbS0NKWlpTV1V4BzRmpqqkaPHq1ly5apsLBQsbGxGjp0qKZOnapu3bo1dfcAAABwDrH4A+UczVRBQYF27tzZ1N0AgFM2dOjQpu7CWeFyubR69eqm7gYAnLL09HRFRkY2dTcAAACaFRZgAQAAAAAAAGAKYSIAAAAAAAAAUwgTAQAAAAAAAJhCmAgAAAAAAADAFMJEAAAAAAAAA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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;</description><pubDate>Wed, 12 Apr 2023 14:19:39 GMT</pubDate><dc:creator>johan.16</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35300.aspx</link><description>&lt;blockquote data-id="35299" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1681308925744" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35299" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35299" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35299" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 4/12/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35299"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35278" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1681306329273" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35278" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35278" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35278" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35278"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35277" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1679926667081" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35277" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35277" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35277" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35277"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35276" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1679924904695" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35276" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35276" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35276" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35276"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35275" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1679924233888" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35275" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35275" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35275" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35275"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1679920996120" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1681308926033" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;a class="if-quote-goto quote-link" href="#" data-id="35275"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Could you please provide code that can actually be parsed error-free? The code relies on images, which you have not provided. There are also a number of elements in the code, such as the "continue" element, which are not defined anywhere in what you provided.&lt;a class="if-quote-goto quote-link" href="#" data-id="35276"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Sorry, please let me know if this works.&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= wrong, Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ shape = rectangle&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ valign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ halign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ color = (255,255,255)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ position = (50,50)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ size = (100%,100%)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;lt;/shape&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35277"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should give you the general idea:&lt;br/&gt;&lt;br/&gt;[code]&amp;lt;values&amp;gt;&lt;br/&gt;/ itemnumber = 1 // will hold the item number for the current round&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;// will hold all vaild response objects for the current trial (wrong is always valid)&lt;br/&gt;&amp;lt;list validresponses&amp;gt;&lt;br/&gt;/ items = ("wrong")&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;// will hold all correct response objects for the current trial&lt;br/&gt;&amp;lt;list correctresponses&amp;gt;&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;    / blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// pick an item number for this round&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.itemnumber = list.Listpick.nextvalue;&lt;br/&gt;]&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ correctresponse = (continue)&lt;br/&gt;/ responsetrial = (continue, Trial_b)&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the trial's stimulus presentation sequence&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.resetstimulusframes();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check which response options are appicable to the selected item and display the applicable ones&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// if the item isn't empty&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ isvalidresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the valid ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ iscorrectresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the correct ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ stimulustimes = [0 = clearscreen, wrong, Digraph_Letter_pic]&lt;br/&gt;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;    / shape = rectangle&lt;br/&gt;    / valign = center&lt;br/&gt;    / halign = center&lt;br/&gt;    / color = (255,255,255)&lt;br/&gt;    / position = (50,50)&lt;br/&gt;    / size = (100%,100%)&lt;br/&gt;    &amp;lt;/shape&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;list Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/list&amp;gt;[/code]&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35278"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Thank you! The test is working as expected with the implementation of lists. But I tried to add values to keep track of incorrect and correct responses.&lt;br/&gt;Here values.total_correct increases by 1 for each correct response, and values.ceil_num_incorrect increases by 1 whenever the "wrong" stimuli is clicked. However, with the current implementation, clicking on "wrong" only increments it once. For further repetition of trials, clicking on "wrong" doesn't change the value anymore. How can that be fixed? I have attached the updated test file below. Thank you once again.&lt;a class="if-quote-goto quote-link" href="#" data-id="35299"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;What, please, is this part below supposed to do?&lt;br/&gt;&lt;br/&gt;[code]&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ ontrialend = [if(trial.Trial_b.response == "Digraph_correct_a1"||"Digraph_correct_a2"|| "Digraph_correct_b1"|| "Digraph_correct_b2"|| "Digraph_correct_c1"||"Digraph_correct_c2"||"Digraph_correct_d1"|| "Digraph_correct_d2"||"Digraph_low_freq_a1"|| "Digraph_low_freq_a2"||"Digraph_low_freq_b1"||"Digraph_low_freq_b2"|| "Digraph_low_freq_c1"|| "Digraph_low_freq_c2" ) {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.total_correct += 1;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.item_count += 1;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.ceil_num_incorrect = 0;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.is_correct = 1;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;}][/code]&lt;br/&gt;&lt;br/&gt;Because, first,&lt;br/&gt;[code](trial.Trial_b.response == "Digraph_correct_a1"||"Digraph_correct_a2"|| "Digraph_correct_b1"|| "Digraph_correct_b2"|| "Digraph_correct_c1"||"Digraph_correct_c2"||"Digraph_correct_d1"|| "Digraph_correct_d2"||"Digraph_low_freq_a1"|| "Digraph_low_freq_a2"||"Digraph_low_freq_b1"||"Digraph_low_freq_b2"|| "Digraph_low_freq_c1"|| "Digraph_low_freq_c2"[/code]&lt;br/&gt;&lt;br/&gt;simply isn't correct syntax and wil always evaluate to true because of that.&lt;br/&gt;&lt;br/&gt;That is also where your problem lies, because that is where you set values.ceil_num_incorrect back to zero in every single trial.&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;</description><pubDate>Wed, 12 Apr 2023 14:19:39 GMT</pubDate><dc:creator>Dave</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35299.aspx</link><description>&lt;blockquote data-id="35278" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" contenteditable="false" id="if_insertedNode_1681306329273"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35278" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35278" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35278" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35278"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35277" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" id="if_insertedNode_1679926667081" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35277" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35277" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35277" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35277"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35276" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" id="if_insertedNode_1679924904695" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35276" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35276" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35276" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35276"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35275" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" id="if_insertedNode_1679924233888" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35275" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35275" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35275" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35275"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" id="if_insertedNode_1679920996120" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1681306330269" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;a class="if-quote-goto quote-link" href="#" data-id="35275"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Could you please provide code that can actually be parsed error-free? The code relies on images, which you have not provided. There are also a number of elements in the code, such as the "continue" element, which are not defined anywhere in what you provided.&lt;a class="if-quote-goto quote-link" href="#" data-id="35276"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Sorry, please let me know if this works.&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= wrong, Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ shape = rectangle&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ valign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ halign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ color = (255,255,255)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ position = (50,50)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ size = (100%,100%)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;lt;/shape&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35277"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should give you the general idea:&lt;br/&gt;&lt;br/&gt;[code]&amp;lt;values&amp;gt;&lt;br/&gt;/ itemnumber = 1 // will hold the item number for the current round&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;// will hold all vaild response objects for the current trial (wrong is always valid)&lt;br/&gt;&amp;lt;list validresponses&amp;gt;&lt;br/&gt;/ items = ("wrong")&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;// will hold all correct response objects for the current trial&lt;br/&gt;&amp;lt;list correctresponses&amp;gt;&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;    / blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// pick an item number for this round&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.itemnumber = list.Listpick.nextvalue;&lt;br/&gt;]&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ correctresponse = (continue)&lt;br/&gt;/ responsetrial = (continue, Trial_b)&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the trial's stimulus presentation sequence&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.resetstimulusframes();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check which response options are appicable to the selected item and display the applicable ones&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// if the item isn't empty&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ isvalidresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the valid ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ iscorrectresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the correct ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ stimulustimes = [0 = clearscreen, wrong, Digraph_Letter_pic]&lt;br/&gt;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;    / shape = rectangle&lt;br/&gt;    / valign = center&lt;br/&gt;    / halign = center&lt;br/&gt;    / color = (255,255,255)&lt;br/&gt;    / position = (50,50)&lt;br/&gt;    / size = (100%,100%)&lt;br/&gt;    &amp;lt;/shape&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;list Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/list&amp;gt;[/code]&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35278"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Thank you! The test is working as expected with the implementation of lists. But I tried to add values to keep track of incorrect and correct responses.&lt;br/&gt;Here values.total_correct increases by 1 for each correct response, and values.ceil_num_incorrect increases by 1 whenever the "wrong" stimuli is clicked. However, with the current implementation, clicking on "wrong" only increments it once. For further repetition of trials, clicking on "wrong" doesn't change the value anymore. How can that be fixed? I have attached the updated test file below. Thank you once again.</description><pubDate>Wed, 12 Apr 2023 13:37:40 GMT</pubDate><dc:creator>johan.16</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35278.aspx</link><description>&lt;blockquote data-id="35277" class="if-quote-wrapper" unselectable="on" data-guid="1679926668763" id="if_insertedNode_1679926667081" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35277" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35277" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35277" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35277"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35276" class="if-quote-wrapper" unselectable="on" data-guid="1679926668763" id="if_insertedNode_1679924904695" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35276" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35276" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35276" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35276"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35275" class="if-quote-wrapper" unselectable="on" data-guid="1679926668763" id="if_insertedNode_1679924233888" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35275" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35275" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35275" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35275"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1679926668763" id="if_insertedNode_1679920996120" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1679926668763" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;a class="if-quote-goto quote-link" href="#" data-id="35275"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Could you please provide code that can actually be parsed error-free? The code relies on images, which you have not provided. There are also a number of elements in the code, such as the "continue" element, which are not defined anywhere in what you provided.&lt;a class="if-quote-goto quote-link" href="#" data-id="35276"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Sorry, please let me know if this works.&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= wrong, Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ shape = rectangle&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ valign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ halign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ color = (255,255,255)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ position = (50,50)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ size = (100%,100%)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;lt;/shape&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35277"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should give you the general idea:&lt;br/&gt;&lt;br/&gt;[code]&amp;lt;values&amp;gt;&lt;br/&gt;/ itemnumber = 1 // will hold the item number for the current round&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;// will hold all vaild response objects for the current trial (wrong is always valid)&lt;br/&gt;&amp;lt;list validresponses&amp;gt;&lt;br/&gt;/ items = ("wrong")&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;// will hold all correct response objects for the current trial&lt;br/&gt;&amp;lt;list correctresponses&amp;gt;&lt;br/&gt;&amp;lt;/list&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;    / blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// pick an item number for this round&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;values.itemnumber = list.Listpick.nextvalue;&lt;br/&gt;]&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ correctresponse = (continue)&lt;br/&gt;/ responsetrial = (continue, Trial_b)&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the trial's stimulus presentation sequence&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.resetstimulusframes();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// reset the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.reset();&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check which response options are appicable to the selected item and display the applicable ones&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// if the item isn't empty&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_correct_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_correct_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_correct_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_a2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_a2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_a2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_b2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_b2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_b2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c1.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c1, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c1");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;if (item.Digraph_low_freq_c2.item(values.itemnumber) != " ") {&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// display the stimulus&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;trial.Trial_b.insertstimulustime(text.Digraph_low_freq_c2, 0);&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// and add it to the lists of valid &amp;amp; correct responses&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.appenditem("Digraph_low_freq_c2");&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;};&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ correctmessage = false&lt;br/&gt;/ errormessage = false&lt;br/&gt;/ pretrialpause = 0&lt;br/&gt;/ posttrialpause = 0&lt;br/&gt;/ recorddata = true&lt;br/&gt;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ isvalidresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the valid ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.validresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;/ iscorrectresponse = [&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// check whether selected response options is among the correct ones for this trial&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;// (this is necessary because even objects that are not on-screen currently can serve as response options)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;list.correctresponses.indexof(trial.Trial_b.response) != -1;&lt;br/&gt;]&lt;br/&gt;/ stimulustimes = [0 = clearscreen, wrong, Digraph_Letter_pic]&lt;br/&gt;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;    / shape = rectangle&lt;br/&gt;    / valign = center&lt;br/&gt;    / halign = center&lt;br/&gt;    / color = (255,255,255)&lt;br/&gt;    / position = (50,50)&lt;br/&gt;    / size = (100%,100%)&lt;br/&gt;    &amp;lt;/shape&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;    &lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = values.itemnumber&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;list Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/list&amp;gt;[/code]&lt;br/&gt;</description><pubDate>Mon, 27 Mar 2023 14:48:04 GMT</pubDate><dc:creator>Dave</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35277.aspx</link><description>&lt;blockquote data-id="35276" class="if-quote-wrapper" unselectable="on" data-guid="1679924905983" contenteditable="false" id="if_insertedNode_1679924904695"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35276" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35276" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35276" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35276"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35275" class="if-quote-wrapper" unselectable="on" data-guid="1679924905983" id="if_insertedNode_1679924233888" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35275" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35275" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35275" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35275"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1679924905983" id="if_insertedNode_1679920996120" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1679924905983" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;a class="if-quote-goto quote-link" href="#" data-id="35275"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Could you please provide code that can actually be parsed error-free? The code relies on images, which you have not provided. There are also a number of elements in the code, such as the "continue" element, which are not defined anywhere in what you provided.&lt;a class="if-quote-goto quote-link" href="#" data-id="35276"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Sorry, please let me know if this works.&lt;br/&gt;&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-5 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen, continue;]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (wrong, Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= wrong, Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape erase_screen&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ shape = rectangle&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ valign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ halign = center&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ color = (255,255,255)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ position = (50,50)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ size = (100%,100%)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;lt;/shape&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text wrong&amp;gt;&lt;br/&gt;/ items = ("WRONG")&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (235,200,235)&lt;br/&gt;/ size = (20%,8%)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = center&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (25,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/ items = ("NEXT")&lt;br/&gt;/ fontstyle = ("Arial", 60, false, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ vjustify = center&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (25,65)&lt;br/&gt;/ size = (20%,15%)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;</description><pubDate>Mon, 27 Mar 2023 13:52:59 GMT</pubDate><dc:creator>johan.16</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35276.aspx</link><description>&lt;blockquote data-id="35275" class="if-quote-wrapper" unselectable="on" data-guid="1679924234454" id="if_insertedNode_1679924233888" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35275" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35275" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35275" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/27/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35275"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1679924234454" id="if_insertedNode_1679920996120" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1679924234454" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; &lt;a class="if-quote-goto quote-link" href="#" data-id="35275"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Could you please provide code that can actually be parsed error-free? The code relies on images, which you have not provided. There are also a number of elements in the code, such as the "continue" element, which are not defined anywhere in what you provided.</description><pubDate>Mon, 27 Mar 2023 13:38:26 GMT</pubDate><dc:creator>Dave</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35275.aspx</link><description>&lt;blockquote data-id="35271" class="if-quote-wrapper" unselectable="on" data-guid="1679920997598" contenteditable="false" id="if_insertedNode_1679920996120"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35271" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35271" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35271" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35271"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1679920997598" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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yDSq0cvJbkPfKDPCUUTrOVPl3zapjKjhozSr3/8a6sL0Z9f+bOe/+fzB3T+qpoq7dq7y1o/+9SzD+g4wOGSm5urcDisjIwMrVixQsuXL9eePc13UexIa9eutaZhbhhg2O12a8Dg5sZ5KSgokNT+6a/Xr18vSe3uAhTfPzk5uV3lAADAkYOgxRCfz6eFCxdaT7ySk5Otmy+Hw6Hk5GSFQiH5/f6WDiNJKi8vV0VFRcLTNb/frz59+sjjaXowU6ApZ0w4w/ocLlyxsMl95izYN63z9y/4fsJ7l51zmSSp3lef0NoiLhQOaf3m2M2E0+HUd0/77kHV1x/wq6K6Qo++8Kgef+lx68nzsAHDEroyxe3cvW/skdTkVKsFzoHomrmv5cem7ZvaXO6isy7S4OMHW+tP/b+ntKWk+W5azQkEAwkzHrU2pTbQFvFpluOvcDhs7NiFhYWy2WyKRCLWeTZv3qwPP/xQ7777rjZs2KD6+vo2PSBoWMemXi217ggGg82WW7BggWbNmqVgMGiFKl277vtddzgccjqdcjqdCV2KGoq3WmlP8FFbW6vKykpFo1ENGTLE2h6JROT1ehUMBhtNux23Y8cOSU23iAEAAEcH/oobUFFRoZUrVyojI8PI8TZtSrzJC4VCys/PV34+4yygfbqkd1G/4/ppw9YN2rpzq3Z/vVvduu4bsNLn91nTJufl5DUKM7419lvKycxRWWWZitcV66IpFyW8X1JaYg2yO2ZY82MVSNKsT2clBCNN2VO+R5u3b04Y+Hbg8QP1woMvNLl/8bp9LcRys3PldjV9o9QW/Xr1s5ZbGs9mf7nZubr75rv1/du/L3/Arx2lO/T7//u9nrj7iXadv95Xr6qaKmt9aP+h7SoPNGXnzp0JN/Q9e/a0WmiYMGrUKJWVlWn9+vVKSUmRzWZTenq60tPTVV5erp07dyotLU1du3ZV7969mz3O8uXLWzxPVlaWBgwY0OR7X375ZbPlbDabsrKyFAqFlJyc3OwxTKqqqtK6devkdDrl9XqVmblvFjSHw6G0tDSFw2Ht2rWr0d/1cDisr7/+2grIAQDA0YmgxYC6urpGLU2i0ajsdrtGjx6t+vp6rVixQtFotNknZvEy8+bNk8PhkM1ms7YlJyfrhBN4uo32y0jLUN/j+mrD1g0KhUP6z+f/0VXnX2W9X+uttaZG/taJ32pUPsmdZE0TPX/5/Ebvv/3R2wpHYk/IRw8d3WJdVq1fpVXrV7W57k6nU7179NbT9zyt3vnN36AdCSaPn6wfXPoDPf7S44pEI3rlvVc0sWiiLj3nUut3uTXx2U/aauuOrRozteVwK+7h2x7Wf039rzYfG52Hw+FI+LtzMK2+mpKUlKSCggIrvFm4cKGqqqrUpUsXRSIReTwehUIh7dixQ1VVVSosbHqw7Jb+Nkott+5wuVwJv2fBYFCRSEQ2m03BYFB1dXUaNmyY0YCpOfX19Vq3Lvad6vV6NXny5IT3nU6n0tLSVFlZqVAopLffflsjR45Ut27dtG3bNq1fv17p6em0XgUA4ChH0GLAunXrEgbECwQC6tmzp/r27Ssp1ux44sSJ8nq9qqmpafY4FRUVjbaFQiGNGNF4bAqgLdwutwoHFOrfn/1bkvTRoo8SgpYvt3yp0q9LZbfbNa5wXKPyHrdHhQML9fmyz7Vm4xqV7i1V99zu1vsffPqBpNg4B6ZaYPTK76WRg0fqjJPP0NnfOtsaM+ZI96PLfqTnXnvOGpz3j8//USeNPEm9C47skAid2+FuDTluXOx7JD6NsdfrVUlJidLS0lRVVaWSkhL17NmzUblRo0Yd8DkHDBiQML5KeXm51qxZY3W/bSlkiXd7aovW9quqqtL69esVjUbl9Xo1duzYJvcbPHiwNm/erO3btysvLy+h1VFqaqp69+6t0tLShGmoAQDA0YW2qQbs/6QtOTm5yX/UpaSkqFu3bo22x9lstoSnjX6/X0OHDmVAPByUk0adZC0vXb1UNXX7wr6/vvVXRSIRJXmSNLjf4EZlbTabVT4UDunlt1623iurLNPSL5ZKij0lb6p8Q7fdcJv2Ltjb6HXXTXclhCnXTb1Oj9/5uC4797JWQ5Ze+b2s5Zq6mgOe8UeStu3cZi0P6NP+7gV5OXm6/9b7rd/hzSWb9dT/e6rN5ZM8SQnXu2HLhhb3dzgc6ta1W7Mv4FAqLS3VwoULG3V1jXO73TruuOM0cOBAnXbaaaqrq5Pb7VZ5efkhr1t2draGDx+ucDgsl8ultWvXNjvrX3xwXK/Xa82itL/4Nbb0oKSyslLLly9XNBpVXV2dJk+e3OzgupLUt29fnXDCCaqoqLDGjqmpqdGkSZOsQXcZ/B4AgKMXQYsB+wchWVlZrTaDbgun06m6urqDPg6ObUVDi5Tkif3D3evzasfu2ECLdd46/fvzWEuXtJS0ZlukjB8x3lqOTwMtSWu/Wmstp6ekW9NCt9dPr/6p3vnzOxoxKNZy674Z9+myn1+m7bu2t1p25KCR1vLeir0HdWOyuWSztTyg74GN43DV+Vfpv763r4vOX/71F733yXttKpuclJwQtKzdtLaFvaWe3Xtq9Turm30Bh1J9fb0ikYh27NjRbIjR0PDhsenT41MlH2pdunTR8ccfr7q6OqWnp2vx4sUt/j3dfzaihlr7O7xt2zYVFxdbg97HW/W0Jj8/X1OmTNGJJ56ooqIinX766ZJkhVF0HwIA4OhF0GJAfGaUhuv7bzuQ4zgcDq1evZqnWjgoqSmpOmXMKZJi4crWHVslxQaSrayOPcE959RzlJbS9NPXrC5ZOvtbsamGS78utQKW+CC6Umx2o3iYcyAGHT9ID9/+sFKSUxSOhDV/+Xzdcv8tqvfVt1juvG+fZy3vKN0hX+DAm9ovW7tvVqX4z+tATLt6mk7oHRtTKRgK6rdP/FalX5e2Wi4jLUPdu+7rlvXp4rZNMQ10BI/HY7XCbEvQEh+w9nA+POjevbuKiooUiURkt9u1devWRvt4PB4lJycrEok0+bc2Go1a23NzcxPei0QiWrlypbZt2yaPx6PU1FRNmDChxZYsgUBAn3/+uRYvXqyqqqom94m3ku3Xr1+T7wMAgCMfQYsB8Smd4w60b3VSUlKjgTOzsrJUXFzc4tSWQGsumXKJpNgUwhu2xrqkfLLok0bvN+fy8y6PlQ8EtPrL1YpEIvpyy76ZPq793rUHXcfRQ0Zr5n0z5XLGxlWYt2ye7p1xb4tlJhZNVH5ebPyJ7bu2a+W6lQd07i82fqE1G9dIinXhmTB6wgEdR5Ly8/J1xw/vsNa3lGzRjJdntFouLSVNRUOLrPWPFn6kiqrG4zYBR4L8/Hz5fD45HA4tXrxYmzZtanYw5zVr1lgPEkzNztdW8RDFbrfr66+/tqZOjovPlOR0OpvsBuX1euX3+xUOh9WjRw9rezgc1tq1a1VbW6tQKKRevXpp2LBhbapTOBxWOBxWSUlJo/d27typPXtiM7kx8xAAAEcv/oobEB9wr+H6pk2brKdg8Sdi27dv17x585o9TkpKirV/Qz6f77D0a0fnVTSsSGmpsaesC1cslM/v0/I1selU83LydGLhiS2WnzB6gnKzcxWOhLVo1SIFQ0Gt37xekpSTmdPq1M5tdebEM63ZccKRsJ597Vm98Z83Wixz2kmnWfv/71P/2+5xWiKRiJ54+QkrzBzSb0hCy5ID8Z3J39F1U6+TzWZTJBrR039/WrMXzG613EVTLrJurnbu2al5y5v/vgDaIt5So+GrueB+//2aejUcEHbSpEmqra1VSkqK9u7dq3fffVfLly+X3+9XMBjUypUrNWvWLFVXV8vpdKq6ulp9+vQ5XJcuKTZWzIQJE+T3++XxeLR79+5GgVDfvn0ViUTkdDr1ySefqLS01Kr/smXLZLfb5Xa7E6ZprqmpUVlZmWw2m/r376+8vLwWf24N65OXlyebzabKykrNnTtXwWBQfr9fs2fP1vbt2+VwOFRTU6Pu3Q/uewgAAHQcZh0y4IQTTtC2bdsSnj7V1tZq0aJF6tGjhyKRiPbs2aNQKNRqn+uxY8dqwYIFCdvcbrfWrFmjvLy8Q1J/dH7pqenqk99Hqzes1oLiBaqpq7FapDQ1rfP+PG6PBvcbrL3lezV/+fxY0LIpFrTEx1Yx5eYrb9bbc97Wrr27JMVm7znrlLOUkpTS5P6XnHOJ/vnBP+X1eVW8tlgvvflSwjgprVn6xVJr9iQp1h3JxExHN199sz6c/6E1yO70F6a3WqZwYKEuOfsS/f3dvysYCuqR5x7R2MKxys3ObbUs0JQdO3ZYM9o01NQ4IsuXL2/1eN27d1fv3vtm0jrxxBO1fPlyuVwu5eXlKRAIqLh4X7fCrKws+Xw+ZWRkaMwYM4HsgcjLy1NZWZkikYg2b96c0C0nJydHmZmZKi8vV1JSkrZu3Wp1M3K73aqvr9eAAQMSxmNbvHix1TqnpKSkydYpDTX8eRcUFKi8vNwaBHfZsli3xbS0NEWjUXk8Ho0fP765QwEAgKMALVoMKCgokN/vb9QSxel0au/evSorK5PD4WjzwHb9+vVr9MQxOTlZn3/++QGN/QKkpaapT0HsSXJlTaX+9eG/tHPPTtlsNn1rTNuClqIhsW4t6zev15uz31RdfWyshYYD0prQI6+H/u93/2fN3rNu0zrd/+T9zXZLGD9ivCaNm2R1u3vg6Qf01bavWv1diUajqvXW6gd3/sCaianvcX017eppRq7juO7H6b+v+2/ZbbGv2WCobWMt3X7j7dYU2l9s+EJTb56q3V/vbvN567x1uuOPd7S+I44J8Zv5/V8NNfV+c6/9u7NkZGTo1FNPVb9+/VReXq76+npr39raWtXW1mr8+PEaNWpUo/M2PPeBcDgccjqdjbrcNqVv375KTk6W2+3W9u2NB9oePHiwBg0apPLycqt1S319verq6jRu3LhGU2RnZ2e36+fWUHp6uk4++WRlZ2eroqJCTqdTDodDZWVl6tWr1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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.&lt;a class="if-quote-goto quote-link" href="#" data-id="35271"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Some irrelevant stimuli have been removed to make the test clutter-free. I'm expanding on what I mentioned before.&lt;br/&gt;You can see here, that in some of the item lists, there is no response. Example: /1 = " ", while some other items have words in them like /2 = "e". This is dependent on the letter/digraph displayed because there are different options for each letter/digraph. The problem is that one letter might have words in the box that is considered a correct response, while some don't have any words at all. So how can that be recorded in a single trial using lists/counters?&amp;nbsp;Is it possible to accommodate these different numbers of responses using a single trial? Or does it have to be done manually with many trials with its own respective letter/digraph?&lt;br/&gt;&lt;br/&gt;Hopefully, the code block below can make a bit more sense. Thank you.&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&amp;lt;expt Update&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ blocks = [1 = general_block]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block general_block&amp;gt;&lt;br/&gt;/ trials = [1-6 = Trial_a]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Trial_a&amp;gt;&lt;br/&gt;  / inputdevice = mouse&lt;br/&gt;  / validresponse = (continue)&lt;br/&gt;  / correctmessage = false&lt;br/&gt;  / errormessage = false&lt;br/&gt;  / correctresponse = (continue)&lt;br/&gt;  / responsetrial = (continue, Digraph_Trial_b)&lt;br/&gt;  / pretrialpause = 0&lt;br/&gt;  / posttrialpause = 0&lt;br/&gt;  / recorddata = true&lt;br/&gt;  / stimulustimes = [1=erase_screen; 20= prompt1_Digraph, prompt2, prompt3, continue]&lt;br/&gt;  &amp;lt;/trial&amp;gt;&lt;br/&gt;  &lt;br/&gt; &amp;lt;trial Trial_b&amp;gt;&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ inputdevice = mouse&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctmessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ errormessage = false&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ pretrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ posttrialpause = 0&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ recorddata = true&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ validresponse = (wrong, name, word, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ correctresponse = (Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (name_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (word_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ responsetrial = (spanish_Digraph, Digraph_Trial_b)&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;/ stimulustimes = [1= Digraph_Letter_pic, Digraph_correct_a1, Digraph_correct_a2, Digraph_correct_b1, Digraph_correct_b2, Digraph_low_freq_a1, Digraph_low_freq_a2, Digraph_low_freq_b1, Digraph_low_freq_b2, Digraph_low_freq_c1, Digraph_low_freq_c2]&lt;br/&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_a1&amp;gt;&lt;br/&gt;/1 = "i"&lt;br/&gt;/2 = "tS"&lt;br/&gt;/3 = "k"&lt;br/&gt;/4 = "dZ"&lt;br/&gt;/5 = "g"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_a2&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_correct_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt; &lt;br/&gt; &amp;lt;item Digraph_correct_b1&amp;gt;&lt;br/&gt;/1 = "eI"&lt;br/&gt;/2 = "k"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "f"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt; &lt;br/&gt;&amp;lt;text Digraph_correct_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_correct_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (200,200,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,18)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_correct_b2&amp;gt;&lt;br/&gt;/1 = "survey"&lt;br/&gt;/2 = "chord"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = "cough"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a1&amp;gt;&lt;br/&gt;/1 = "geyser"&lt;br/&gt;/2 = "S"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_a2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_a2&amp;gt;&lt;br/&gt;/1 = "al"&lt;br/&gt;/2 = "machine"&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (27,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b1&amp;gt;&lt;br/&gt;/1 = "E"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_b2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (32,45)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_b2&amp;gt;&lt;br/&gt;/1 = "eyrie"&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c1&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Ipa-samd Uclphon1 SILDoulosL", 50, false, false, false, false, 5, 2)&lt;br/&gt;/ size = (5%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (2,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c1&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = " "&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/ items = item.Digraph_low_freq_c2&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("Arial", 40, false, false, false, false, 5, 0)&lt;br/&gt;/ size = (16%,8%)&lt;br/&gt;/ txbgcolor = (235,235,200)&lt;br/&gt;/ txcolor = (0,0,0)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (7,57)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_low_freq_c2&amp;gt;&lt;br/&gt;/1 = " "&lt;br/&gt;/2 = " "&lt;br/&gt;/3 = " "&lt;br/&gt;/4 = "test"&lt;br/&gt;/5 = " "&lt;br/&gt;&amp;lt;/item&amp;gt; &lt;br/&gt;&lt;br/&gt;&amp;lt;text Digraph_Letter&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ fontstyle = ("ABCPrint", 30, true, false, false, false, 5, 0)&lt;br/&gt;/ txbgcolor = (transparent)&lt;br/&gt;/ size = (8%,8%)&lt;br/&gt;/ txcolor = (200,200,200)&lt;br/&gt;/ halign = left&lt;br/&gt;/ vjustify= center&lt;br/&gt;/ position = (4,5)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter&amp;gt;&lt;br/&gt;/1 = "ey"&lt;br/&gt;/2 = "ch"&lt;br/&gt;/3 = "ck"&lt;br/&gt;/4 = "dg"&lt;br/&gt;/5 = "gh"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture Digraph_Letter_pic&amp;gt;&lt;br/&gt;/ items = item.Digraph_Letter_pic&lt;br/&gt;/ select = counter.Listpick&lt;br/&gt;/ valign = center&lt;br/&gt;/ halign = center&lt;br/&gt;/ position = (75,50)&lt;br/&gt;/ size = (60%,60%)&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt; &amp;lt;item Digraph_Letter_pic&amp;gt;&lt;br/&gt;/1 = "pic1.jpg"&lt;br/&gt;/2 = "pic2.jpg"&lt;br/&gt;/3 = "pic3.jpg"&lt;br/&gt;/4 = "pic4.jpg"&lt;br/&gt;/5 = "pic5.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;counter Listpick&amp;gt;&lt;br/&gt;/ items = (1,2,3,4,5)&lt;br/&gt;/ select = sequence&lt;br/&gt;&amp;lt;/counter&amp;gt;&lt;br/&gt;&lt;br/&gt;------------------------------------------------------------------------------------------------------&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt; </description><pubDate>Mon, 27 Mar 2023 13:30:57 GMT</pubDate><dc:creator>johan.16</dc:creator></item><item><title>RE: Is it possible to refactor this test using 1 trial with item lists?</title><link>https://forums.millisecond.com/Topic35271.aspx</link><description>&lt;blockquote data-id="35269" class="if-quote-wrapper" unselectable="on" data-guid="1679672030558" id="if_insertedNode_1679672028918" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="35269" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="35269" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="35269" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;johan.16 - 3/24/2023&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-35269"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hello everyone. I am having trouble incorporating item/lists format for this Inquisit test.In this specific case, we have grey colored boxes with correct responses, and light yellow boxes with ‘low frequency’ correct responses. There is also a ‘wrong’ button to indicate an incorrect response. For each letter displayed, the amount of responses available may vary in both correct and low freq correct responses.&amp;nbsp;For example, in the images attached below, the letter 'ck' has only one response&amp;nbsp;while 'ey' has 4 responses. Some of the boxes are empty because there are no responses for the associated letter. &lt;br/&gt;&lt;br/&gt;So if we use item lists, one of the item elements would be an empty string /1 = " " if there are no correct responses. But all the boxes are considered correct responses.&lt;br/&gt;&lt;br/&gt;&lt;img 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alt=""&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;Is it possible to accommodate these different numbers of responses using a single trial? The number of correct and low-frequency responses varies item by item, and we're trying to avoid coding 100 individually scripted trials.&lt;br/&gt;&lt;br/&gt;&lt;a class="if-mention if-mention-disabled" href="https://forums.millisecond.com/UserInfo6063.aspx"&gt;@jmwotw&lt;/a&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="35269"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;This should be possible, but for concrete advice you'll have to provide some actual code. I have no idea what you have and how you've set it up based an a bunch of images.</description><pubDate>Fri, 24 Mar 2023 15:34:37 GMT</pubDate><dc:creator>Dave</dc:creator></item></channel></rss>