Dear all,
I would like to create a Bayesian linear mixed model for repeated measurements (visits) with a random intercept for subjects.
I have 2 treatments (Placebo and Active).
I have also interaction between treatment and visits and I would like to add a prior distribution for the placebo effect.
I am using the proc mcmc but I am not sure how to add the prior distribution for the placebo effect.
I should create one indicator variable for treatment (1=active, 0=placebo) but for which beta I should specify the prior distribution? Y=B0 + B1*treatment+ B2*Visit + B3*Visit*treatment
Is it for B0 only in this case?
or should I create 2 indicator variables: placebo (1, otherwise 0) and active (1, otherwise 0) and then add the prior distribution for the beta related to placebo indicator variable and for the beta related to the placebo indicator*visit variable?
Thank you in advance,
Best regards,
Clemence
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