[R] can I get same results using lme and gls?

[toby909 at gmail.com]

Hi All

I was wondering how to get the same results with gls and lme. In my lme, the 
design matrix for the random effects is (should be) a identity matrix and 
therefore G should add up with R to produce the R matrix that gls would report 
(V=ZGZ'+R). Added complexity is that I have 3 levels, so I have R, G and say H 
(V=WHW'+ZGZ'+R). The lme is giving me the correct results, I am having trouble 
finding the right corresponding specification for the gls.

Thanks for your help.

Toby


dtaa = 
read.table("http://www.ats.ucla.edu/stat/mplus/examples/ma_snijders/mlbook1.dat", 
sep=",")
dta1 = reshape(dtaa, list(c("V10","V12")), "score", direction="long", 
drop=c("V2","V3","V4","V5","V6","V7","V8","V9","V11","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25"))
colnames(dta1)[1] = "schoolNR"
dta2 = dta1[order(dta1$id),]
head(dta2)
timef = factor(dta2$time)

summary(mdl1l <- lme(score~timef-1, dta2, ~timef-1|schoolNR/id,,,,"ML"))
summary(mdl1g <- gls(score~timef-1, dta2, corCompSymm(, ~timef|schoolNR/id), 
varIdent(, ~1|id*timef),,"ML"))