Hello,   I'm looking for advice/feedback about analyzing data from a treatment study. The outcome was a frequency count of conduct problems collected each day for 40 days. A within-persons design was used, with one treatment implemented for the first 20 days and a second treatment implemented the last 20 days (order was counterbalanced across participants). The primary test of interest is a personality x treatment interaction, where personality is a continuous measure collected prior to the onset of treatment. Time is not really a variable of interest, but since data were collected over time I think it needs to be taken into account in the analyses.   Here are some of my other thoughts about the statistical model/code: 1. The outcome is a count so use glimmix to fit a negative binomial model 2. Time consists of 40 repeated measures (day 1 to 40) so time should be a continuous measure 3.  There seemed to be lots of variance acros participants and across days so include a random intercept and slope.   With those thoughts in mind, here is the syntax I've come up with: proc glimmix data=work.temp ; title1 'Conduct Problems outcome'; class ID treatment; model CondProb_sum = time personality|treatment / solution dist=negbin link=log ddfm=bw; random intercept time /subject=id type = chol; nloptions maxiter=200 tech=nrridg; lsmeans treatment / ilink; run; In the above code: Treatment = 0 (standard treatment) vs. 1 (modified treatment) Personality = continuous score collected at baseline and centered at the sample mean Time = day in treatment ranging from -39 (first day of treatment) to 0 (last day of treatment)   I'm not a statistician and I'm relatively new to SAS so any advice, thoughts, feedback, etc. on any of this is greatly appreciated. Thanks in advance.   -DW   ... View more