> I've successfully implemented 3dlmer for longitudinal models where I've include both an age and age2 term
> (continuous, quantitative measure) and assessed gender differences (binary 0/1 coding).

Did you really code gender as 0/1 instead of a factor?

> -gltCode age2.rew-pun.cort 'task : 1*rew -1*pun cortisol : age2 : ' \

This inference does not make sense: what does it mean when you want to obtain both slope effects at the same time?

> -gltCode Val_age2med 'task : 1*rew +1*pun cortisol : 5 age2 : 60' \

This one is meaningful, but 3dLMEr currently does not support it. One workaround solution is to center one variable around the value you are interested (e.g., cortisol at 5), and then try

-gltCode Val_age2med 'task : 1*rew +1*pun cortisol : 5 age2 : 60' \
(Note: age2 at 60 should be relative to the centered age value)

Or center both variables (e.g., e.g., cortisol at 5 age2 at 60), and add

-gltCode Val_age2med 'task : 1*rew +1*pun'

Gang



Edited 2 time(s). Last edit at 01/28/2021 08:43AM by Gang.