Dear Alfonso,
I ran an FC-MVPA followed by post-hoc analyses to identify predictors of treatment response, using baseline rs-fMRI data only. The sample includes 86 participants: approximately half received treatment A&B and the remainder received A&placebo, 40 were responders and 46 non-responders.
Given that our analyses of treatment efficacy did not show differences between treatment arms, I did not initially account for treatment allocation. Accordingly, the main contrast was responders (to either treatment) versus non-responders (to either treatment).
I have now received a comment
asking to run another post-hoc analysis to demonstrate that
treatment allocation didn't influence the results. Do you know
what's the simplest way to address or demonstrate this?
I considered including treatment allocation (A&B vs
A&placebo) as covariates, but I am unsure which contrast would
best answer this question (I know I can always rerun all of my
analyses controlling for treatment allocation, but I'm unsure how
I'd compare these results to my previous ones, as I have many
resulting clusters).
The model would include these covariates: Responders, Non-responders, Treatment A&B, Treatment A&placebo.
Many thanks for your help.
Best,
