AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

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July 17, 2017 06:17PM
Dear Gang,

I have a modelling question about 3dLME. The help page mostly describes between-subjects designs, but I was wondering about cases with within-subjects design. My main interest is on a correlation analysis between brain and behavioral data in respect to within-subjects conditions.

I have a 2 x 2 design -- both factors are within-subjects contrasts (i.e., 2 treatments and 2 cue conditions).
- There are several covariates of no interests that I would like to control (e.g., between-subjects and within-subjects covariates of no interest, such as body mass and session order; all centered at grand average).
- Because both the behavioral and brain data would be affected by these covariates of no interests, I first residualized the behavioral data using lme framework: RT ~ body mass + session order + (1|subj) — including all data points from 2 x 2 conditions (i.e., 4 data points / subject).

Constructing 3dLME, my full model is y (brain) ~ treatment * cue * RT (residual) + body mass + session order + (1|subj).
I also added GLTs to observe how within-subjects factor/level interacts/correlates with RTs. For instance, given a specific treatment condition, I tested the effect of RT, or tested treatment * RT:
-gltLabel 1 ‘DD_RT’ -gltCode 1 ‘treatment : 1*DD RT : ’ \
-gltLabel 2 ‘PC_RT’ -gltCode 2 ‘treatment : 1*PC RT : ’ \
-gltLabel 3 ‘treatment_x_RT’ -gltCode 3 ‘treatment : 1*DD -1*PC RT : ’ \


The part that I am uncertain is that the correlation analyses (GLTs) are between-subjects (across participants). But the actual data points in brain and RT are now centered at each subject’s mean (b/c of random intercept of subjects), such that the actual variation across subjects are removed. So my GLTs are testing the relationship between subject-wise relative changes of RTs and brain/voxels in a specific condition across subjects. I am not sure if this is the right approach to test the correlation with quantitative data.

I am using 3dLME because I have to control covariates of no interest (covs that are both between-subjects and within-subjects). And behavioral data is collected during scanning, so I wanted to control these covariates from both behavior and brain.

Your feedback would be greatly appreciated. Thank you!
Best, Michelle
Subject Author Posted

Quantitative factor in LME (within-subjects conditions)

sjmich July 17, 2017 06:17PM

Re: Quantitative factor in LME (within-subjects conditions)

gang July 19, 2017 01:12AM

Re: Quantitative factor in LME (within-subjects conditions)

sjmich July 19, 2017 07:37PM

Re: Quantitative factor in LME (within-subjects conditions)

gang July 21, 2017 11:38AM

Re: Quantitative factor in LME (within-subjects conditions)

sjmich July 21, 2017 06:14PM

Re: Quantitative factor in LME (within-subjects conditions)

gang July 21, 2017 06:34PM