Hi all,
I'm relatively new to the world of SAS - I have some experience running PROC MIXED but have not needed to use SAS all too much throughout my graduate training. Here's a summary of my data that is being used for my dissertation:
- Approximately 50 youth, diagnosed with certain mental health disorders, who were a part of an intensive, 5-week treatment program
- The outcome of interest is aggression which is a continuous, non-negative, count variable and is showing a negative binomial distribution (highly positively skewed with var > mean). This outcome was measured across the 5 weeks - thus, each child has a weekly aggression score
- This outcome is showing a highly skewed distribution across the 5 weeks
- I am interested in whether certain pre-treatment affective states (e.g., irritability) predict changes in the intercept and slope/trajectory of aggression across the 5 treatment weeks
- Importantly, treatment did NOT differ across youth; they all received the same treatment
The various resources I have read online suggest PROC GLIMMIX to be the ideal approach but the issue I am running into is that every single resource/example implies that GLIMMIX is best suited for clustered data where participants are separated into various conditions. Again, that is not the case for my data. I have scores nested within youth but that is it.
I've consulted various resources and have piecemealed syntax that runs a converging model without errors (all predictors have been centered hence the 'c'):
PROC GLIMMIX DATA = diss.stplong method=quad;
Class STPID;
Model CPsum = cirr clpe cweek / s link=log dist=negbin;
Random intercept / sub = STPID;
Run;
I removed the random effect of week from the RANDOM statement as that led to the estimated G matrix being not positive definite. I'd appreciate any/all feedback. Apologies for the long post and sorry for any elementary mistakes I've made in this.
Thanks so much.
-Pev.
