Back to PLS HelpPosted on 12/02/16 16:33:08
Number of posts: 4
Hi, thanks for hosting this message board. It's a very useful resource. I have a question about how to organize the behavioral data to look for relationships with the ERP data. More specifically, how should one organize the behavioral data when there the "conditions" for the ERP data are not mirrored in the behavioral data.
Concretely, the ERP data is from three different groups of ten subjects each, with each subject having ERPs recorded in ten different conditions involving speech token stimuli in various types and levels of background noise. Then for each subject there are scores from 13 different behavioral measures related to speech in noise, which do not correspond to the 10 conditions.
Any advice on how to handle this would be much appreciated.
Thanks,
Brandon
Replies:
Posted on 12/03/16 07:28:28
Number of posts: 394
Hi, thanks for hosting this message board. It's a very useful resource. I have a question about how to organize the behavioral data to look for relationships with the ERP data. More specifically, how should one organize the behavioral data when there the "conditions" for the ERP data are not mirrored in the behavioral data.
Concretely, the ERP data is from three different groups of ten subjects each, with each subject having ERPs recorded in ten different conditions involving speech token stimuli in various types and levels of background noise. Then for each subject there are scores from 13 different behavioral measures related to speech in noise, which do not correspond to the 10 conditions.
Any advice on how to handle this would be much appreciated.
Thanks,
Brandon
Hi Brandon,
The easiest way, but most complex from the analytic output, is to repeat the 13 behavior measures for each of the conditions. That will give 130 potential LVs to interpret. If there are ways to reduce the space and focus the analysis, that may help. For example, can you do a PCA on the behaviors to reduce the dimensionality? Alternatively, take an average of the 10 condtions (perhaps weighted by the contrasts you get from a task PLS) and do the behavior analysis on that.
Posted on 12/05/16 11:54:22
Number of posts: 4
Thank you; that is helpful. One follow-up question is: in terms of the structure when I'm making the behavioral datamat, should it be input as 2-dimensional and stacked, or does the program expect it to be of a higher dimension so that it can create the stacked version itself?
Posted on 12/05/16 11:56:06
Number of posts: 394
Thank you; that is helpful. One follow-up question is: in terms of the structure when I'm making the behavioral datamat, should it be input as 2-dimensional and stacked, or does the program expect it to be of a higher dimension so that it can create the stacked version itself?
2 dimensional already stacked
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