While working through the text "Applied Longitudinal Analysis" by
Fitzmaurice, Laird and Ware, I encountered a fairly simple case study (pp
210-7) in which a longitudinal model specifies three random effects: (1)
random intercepts for id, (2) random slopes for covariate1 (Age | id), and
(3) random slopes for covariate2 (log(ht) | id).  I've had no difficulty
formulating lmer models with correlated random intercepts and slopes for
either of the covariates individually but have not succeeded when I try to
compose a model with correlated random intercepts and slopes for two
covariates.

 

Following is code that works well with the individual covariates separately:

 

m1=lmer(LFEV1~Age + loght + InitAge + logbht + (1 + Age | id),data=fev,

       na.action=na.omit, method="REML")

 

m2=lmer(LFEV1~Age + loght + InitAge + logbht+(1 + loght | id),data=fev,

       na.action=na.omit, method="REML")

 

I have yet to write code that succeeds with both covariates simultaneously.
I am running V 2.5.1 of R and the most recent version of lme4.

 

Any advice will be appreciated. If more detail is needed, I can send it but
thought this might be sufficient to pose the problem.

 


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