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I have 139 subjects (ID), with measurements taken at two time points (Time1, Time2), at 148 brain regions, a dependent measure called volume, and a covariate called thickness.

Each subject has 148 brain regions with volume and thickness measured twice

I am trying to find out if there is a difference in volume between timepoint 1 and timepoint 2 while controlling for thickness. I want to know which brain regions show this difference. I need help setting up the contrasts.

I am using R. and trying to figure out a model with linear mixed models with (1|ID) as random factor, fixed factors regions, thickness. I have timepoint as factor with two levels 1 and 2

Data is longitudinally organized. Do i need to organize the regions by factors? I have them as Region 1,2,3,4 etc

Model lmer(volume ~ time*region + thickness + (1|ID) 

How do i set up the contrasts and post hoc to find out regional differences in volume?

Thank you!

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I have 139 subjects (ID), with measurements taken at two time points (Time1, Time2), at 148 brain regions, a dependent measure called volume, and a covariate called thickness.

Each subject has 148 brain regions with volume and thickness measured twice

I am trying to find out if there is a difference in volume between timepoint 1 and timepoint 2 while controlling for thickness. I want to know which brain regions show this difference. I need help setting up the contrasts.

I am using R. and trying to figure out a model with linear mixed models with (1|ID) as random factor, fixed factors regions, thickness. I have timepoint as factor with two levels 1 and 2

Data is longitudinally organized. Do I need to organize the regions by factors? I have them as Region 1,2,3,4 etc.

Model lmer(volume ~ time * region + thickness + (1 | ID) 

How do I set up the contrasts and post hoc to find out regional differences in volume?