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code for mixed model in R?

2 messages · jurgen_vercauteren, Ben Bolker

#
Dear

I am analysing my data wit a mixed model. I used SAS but I want to redo the
same analysis in R. Here the SAS code and what I wrote in R. It seems to
work but the results are not the same. I don't know how to specify the class
variable in R or specify the variance matrix. Can you please help me?

Thanks
Jurgen

## SAS:
proc glimmix data=trend method=RSPL;
   class pid;
   model mdrfinal (event = '1') = time therapy comment / dist=binary
link=logit solution cl;
   random intercept / subject=pid type=un;
run;

## R:
model_GLMM<- glmmPQL(mdrfinal ~ time + therapy + comment, data = data,
family = binomial, random = ~1| time)
summary(model_GLMM) 

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#
jurgen_vercauteren <jurgen_vercauteren <at> hotmail.com> writes:
This question would probably get a better reception on the r-sig-mixed-models
<at> r-project.org mailing list.

  I think you want random = ~1|pid , although with an unstructured
variance-covariance matrix you may want random=~factor(time)|pid --
keep in mind that's what on the RHS of the bar is a grouping factor,
the LHS of the bar is the random effect(s) term.

  If you do ~1|pid you'll get a compound-symmetry model with positive rho;
if ftime is a factor variable and you do ~ftime|pid you'll get an
unstructured matrix.