How should I specify partially crossed random effects in lme?
You are more likely to get a useful response on the r-sig-mixed-models list rather than here. Cheers, Bert
On Sat, Nov 23, 2013 at 9:04 PM, Pradeep Babu S. <pradeep.babu at gmail.com> wrote:
Dear all,
I am new to R and would like your help with lme formula for partially
crossed random effect in a random-intercept, random-slope model.
In the longitudinal data I have, each subject (barring some dropouts) was
tested at 5 different occasions. The standardized tests were administered
by 3 different examiners, with 2 of them present at all occasions, and the
3rd one administering tests only on the last two occasions. The subjects
were randomly assigned to the examiners.
I tested the following models:
model1<-lme(score~time*covariate,random=~time|subject,method="REML",na.action=na.omit,data=dat)
model2<-lme(score~time*covariate,random=list(examiner=~1,subject=~time),method="REML",na.action=na.omit,data=dat)
anova(model1,model2) gives p<0.05 with better model fit for model2.
I would like to know if model2 is the correct way to specify the partially
crossed random effect in the data I described.
thanks!
Pradeep Babu
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Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374