Programming the statistical procedures from SAS

how to adjust for several covariates in mixed model (baseline adjustments)

Reply
New User
Posts: 1

how to adjust for several covariates in mixed model (baseline adjustments)

In a placebo controlled randomized study invesigating the effect of a drug on weight, blood pressure ect, I found that there is difference in the baseline weight between the two groups (placebo group and active group).

The study has repeated measurements ,and therefore I am using mixed model. To adjust for baseline difference in my outcome weight, I have build this model:

 

proc mixed data=sasuser.data;

WHERE week > 0;

class id week treat (ref='2');

model weight = week treat treat*week weight0*treat

              /solution CL DDFM=KR;

repeated week / subject=id type=un r rcorr;

run;

 

where weight0 is mean weight at baseline for both groups. As far as I understand, I put it as a covariate (ANCOVA).

 

However, I want to adjust for other baseline differences, such as age and gender. My question is therefore: How do I do that in the model above? Can I have more than one covariate at the same time?

 

THANK YOU!

  

Respected Advisor
Posts: 2,655

Re: how to adjust for several covariates in mixed model (baseline adjustments)

Yes, you may have more than one covariate (although gender would most likely be included in the CLASS statement as a categorical covariate).  Get a copy of SAS for Mixed Models, 2nd ed. by Littell et al., and look at Chapter 7 Analysis of Covariance for very good coverage of this subject.

 

Steve Denham

Frequent Contributor
Frequent Contributor
Posts: 134

Re: how to adjust for several covariates in mixed model (baseline adjustments)

You want to use the values of the covariates for each subject (ID), not the group means.

 

With multiple covariates, I find it useful to remember that my model is now a multiple regression, with all the assumptions and issues associated with multiple regression (multicollinearity, influence, etc.). So in addition to Steve's suggestions (the "bible" for mixed models in SAS, always a good idea), read up on multiple regression. 

 

Walt Stroup told me this week that the 3rd edition could be out this year. Which would be swell.

Ask a Question
Discussion stats
  • 2 replies
  • 333 views
  • 1 like
  • 3 in conversation