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

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

CamillaSvensson — Thu, 28 Apr 2016 11:58:25 GMT

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!

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

SteveDenham — Thu, 05 May 2016 13:11:17 GMT

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

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

sld — Fri, 06 May 2016 19:57:34 GMT

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.

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

PSZ — Wed, 28 Nov 2018 21:03:41 GMT

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