topic Re: Normality Assumption for Mixed Model Analysis in Statistical Procedures

Normality Assumption for Mixed Model Analysis

twix17 — Tue, 21 Jun 2022 17:26:35 GMT

Hello community,

I am doing some analysis for repeated measure data and using a mixed model method to carry out my analysis to accommodate missing data. Below are my lines of code and i have also attached the sample data

proc mixed data=data;
class trt sub time (ref=first);
model Y = time trt time*trt/ s chisq;
repeated / type=un subject=sub r;
run;

I understand I needed to carry out model diagnostic before for modelling my data. Can anyone help on how I can perform Normality Assumption for my data with SAS code.

Thanks

Re: Normality Assumption for Mixed Model Analysis

PaigeMiller — Tue, 21 Jun 2022 18:08:14 GMT

My understanding is different. You test the normality assumption AFTER you fit the model, by seeing if the residuals are normally distributed. There is no need for the response or predictor variables to have a normal distribution.

Re: Normality Assumption for Mixed Model Analysis

lvm — Thu, 23 Jun 2022 17:29:49 GMT

Best approach is to look at the studentized residuals in graphic form. Add PLOTS=studentpanel on the procedure statement. See the user guide about how to interpret. Normality is not overly important (within reason), but constant variability is important.

Re: Normality Assumption for Mixed Model Analysis

lvm — Thu, 23 Jun 2022 17:37:09 GMT

Your choice of an unstructured covariance matrix (UN) could be problematic if you have many times. The number of parameters to estimate for variances and covariances grows geometrically with time. I recommend you check out the user's guide for examples of other choices for type=.

The second example in the MIXED user's guide is a good place to start, if you haven't already read it. Or read:

https://www.jstor.org/stable/1400366?seq=1

Re: Normality Assumption for Mixed Model Analysis

twix17 — Sun, 26 Jun 2022 18:55:42 GMT

Thank you. I find this information helpful and implemented the suggestion.