[R-sig-ME] factor specific residual variance for random coefficient model with lmer

[li li]

Hi all,
  I am wondering how to specify the model fm1 below so that the two
groups (treatment and control) specified by the column drug in the
data matrix have different residual variances. Any suggestion?
  Please see the codes below.
  Thanks very much!
    Hanna




set.seed(500)
n.timepoints <- 8
n.subj.per.tx <- 20
sd.d <- 5;
sd.p <- 2;
sd.res <- 1.3
drug <- factor(rep(c("D", "P"), each = n.timepoints, times =
n.subj.per.tx))
drug.baseline <- rep( c(0,5), each=n.timepoints, times=n.subj.per.tx )
Patient <- rep(1:(n.subj.per.tx*2), each = n.timepoints)
Patient.baseline <- rep( rnorm( n.subj.per.tx*2, sd=c(sd.d, sd.p) ),
each=n.timepoints )
time <- factor(paste("Time-", rep(1:n.timepoints, n.subj.per.tx*2),
sep=""))
time.baseline <-
rep(1:n.timepoints,n.subj.per.tx*2)*as.numeric(drug=="D")
dv <- rnorm( n.subj.per.tx*n.timepoints*2,
mean=time.baseline+Patient.baseline+drug.baseline, sd=sd.res )
dat.new <- data.frame(time, drug, dv, Patient)
dat.new$time.num = rep(1:n.timepoints, n.subj.per.tx*2)

library(lme4)
fm1 <- lmer( dv ~ time.num*drug + (0+ drug + time.num | Patient ),
data=dat.new )
summary(fm1)
resid(fm1)
plot(resid(fm1))