All,
 
How does one specify a model in lmer such that say the random effect for

the intercept has a different variance per treatment group?  
Thus, in the model equation, we'd have say b_ij represent the random
effect
for patient j in treatment group i, with variance depending on i, i.e,
var(b_ij) = tau_i.
 
Didn't see this in the docs or Pinherio & Bates (section 5.2 is specific
for 
modelling within group errors).  Sample repeated measures code below is
for 
a single random effect variance, where the random effect corresponds to
patient.
cheers,
dave
 
 
z <- rnorm(24, mean=0, sd=1)
time <- factor(paste("Time-", rep(1:6, 4), sep="")) 
Patient <- rep(1:4, each = 6) 
drug <- factor(rep(c("D", "P"), each = 6, times = 2)) ## P = placebo, D
= Drug
dat.new <- data.frame(time, drug, z, Patient) 
fm =  lmer(z ~ drug + time + (1 | Patient), data = dat.new )

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