Hi. I have a question about the data analysis.

Can I make custom algorithms for data analysis?

1) The measures are the accuracy and latency of each trials, but I need mean reaction time of each trial code (only for correct response).

2) I don't know how to except incorrect data or how to compute the percentage of accuracy so that I can eliminate data with extremely inaccuracy data. Can I do that in Inquisit program?

3) The SRC task is conducted twice (pre_SRC → Treatment → post_SRC) and  I measure the difference of approach tendency as DV. The calculation is the following.

[post_SRC (approach_mean RT) - (avoidance_mean RT)]  -  [pre_SRC (approach_mean RT) - (avoidance_mean RT)]

for smoking_trials and control_trials, respectively.


Thanks for your help.

All of that can be easily computed in any proper data analysis software based on the raw data provided by Inquisit. This may be the preferable route to take if you are not familiar with Inquisit's syntax.

Beyond that, it is also possible to have Inquisit directly aggregate and record most of the aggregate measures you need by either logging suitable properties to the data file or implementing the computations yourself via <values>, <expressions> and conditional logic in event attributes.

See the properties listings for <trial>, <block> and <expt> elements in the documentation. See the documentation for the <data> element's /columns attribute. See the documenation for <values>, <expressions>, operators, functions and conditional logic.

Please note: None of this is for absolute beginners -- you must make sure to have a solid grip on Inquisit / its syntax first.