[R-sig-ME] Package for GLMM with correlation matrix

wong aspxwong at gmail.com
Fri Oct 22 11:35:00 CEST 2010


I'm looking for a R package for fitting a generalized linear mixed model
where g is a link function, β is a p vector of fixed effects, u is a
vector of random effects, X is design matrix, Z is an identity matrix.
In our data, each individual has only one observation for response y.
Because individuals may be correlated in some way, leading to similar
reponses, random effect u is employed to correct for individual
background effect. The variance of u is assumed to be Var[u]=G*σ^2, in
which G is a correlation matrix.

glmmPQL in MASS has an argument for correlation. However, I
encountered an error of invalid formula when using a n*n dimension
matrix G (n is the number of individuals, and also the length of y)
for argument 'correlation' in glmmPQL. For example:

> y=sample(c(1,0),48,replace=T);x=sample(1:4,48,replace=T);id=1:48;covMat=matrix(rnorm(48*48),nrow=48)
> glmmPQL(y~x,random=~1|id,family=binomial,correlation=covMat)
iteration 1
Error in formula.default(object) : invalid formula

The R help documentation for glmmPQL is very compact. No detailed
explanation. Does anybody know how to use correlation matrix in
glmmPQL? Is it good to use glmmPQL for fitting my model?



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