automatic allotment of participants across various conditions


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abhi
abhi
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Hi,
1  ) I have 4 expt conditions ( am using - 1 of 4 , 2 of 4, 3 of 4 and 4 of 4  for participant allotment) with random assignment in expt element.

Problem is that many participants drop out before completing the expt. In that case will I have unequal allotment of participants across 4 conditions ?

If that is so, how to ensure that equal number of participants complete the  study across all 4 conditions ?

2 ) I have 4 blocks in each study . One participant informed me that after each block completion Inquisit asked 'whether he wants data to be saved on computer '  ? I was wondering how can this happen ? (it was an online/ web study )

Thanks

Dave
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abhi - Thursday, November 10, 2016
Hi,
1  ) I have 4 expt conditions ( am using - 1 of 4 , 2 of 4, 3 of 4 and 4 of 4  for participant allotment) with random assignment in expt element.

Problem is that many participants drop out before completing the expt. In that case will I have unequal allotment of participants across 4 conditions ?

If that is so, how to ensure that equal number of participants complete the  study across all 4 conditions ?

2 ) I have 4 blocks in each study . One participant informed me that after each block completion Inquisit asked 'whether he wants data to be saved on computer '  ? I was wondering how can this happen ? (it was an online/ web study )

Thanks

Re. #1:
> Problem is that many participants drop out before completing the expt. In that case will I have unequal allotment of participants across 4 conditions?
Yes.
> If that is so, how to ensure that equal number of participants complete the  study across all 4 conditions ?
Only option I can see is to remove the conditions that are already "full", and only keep running those that are not until you have an approximately equal amount in each condition.

Re. #2:
> One participant informed me that after each block completion Inquisit asked 'whether he wants data to be saved on computer '  ?

This is Inquisit's fallback option when it is not possible to transmit the data from the participant's computer to the server because the participant's internet connection went down (or something like a misconfigured firewall, etc. blocked the communication with the server). Participants are then prompted to save the data locally to prevent data loss and contact the researcher running the study.

Hope this helps.


abhi
abhi
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Dave - Friday, November 11, 2016
abhi - Thursday, November 10, 2016
Hi,
1  ) I have 4 expt conditions ( am using - 1 of 4 , 2 of 4, 3 of 4 and 4 of 4  for participant allotment) with random assignment in expt element.

Problem is that many participants drop out before completing the expt. In that case will I have unequal allotment of participants across 4 conditions ?

If that is so, how to ensure that equal number of participants complete the  study across all 4 conditions ?

2 ) I have 4 blocks in each study . One participant informed me that after each block completion Inquisit asked 'whether he wants data to be saved on computer '  ? I was wondering how can this happen ? (it was an online/ web study )

Thanks

Re. #1:
> Problem is that many participants drop out before completing the expt. In that case will I have unequal allotment of participants across 4 conditions?
Yes.
> If that is so, how to ensure that equal number of participants complete the  study across all 4 conditions ?
Only option I can see is to remove the conditions that are already "full", and only keep running those that are not until you have an approximately equal amount in each condition.

Re. #2:
> One participant informed me that after each block completion Inquisit asked 'whether he wants data to be saved on computer '  ?

This is Inquisit's fallback option when it is not possible to transmit the data from the participant's computer to the server because the participant's internet connection went down (or something like a misconfigured firewall, etc. blocked the communication with the server). Participants are then prompted to save the data locally to prevent data loss and contact the researcher running the study.

Hope this helps.


Thanks for this Dave

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