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

[CamillaSvensson]

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!

[SteveDenham]

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

[sld]

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.

[PSZ]

Have you got the answer for your question?

I have a question about your data set. Did you add your baseline weight for the follow up studies? For example:

person    visit                    group             weight                                                   bloodpressure

1             baseline             placebo         baseline weight                                      100

2             baseline              active             baseline weight                                      101

1             visit1                  placebo         baseline weight or visit1 weight?            100

2            visit1                  active              baseline weight or visit1 weight?             101