maintaining specified factor contrasts when subsetting in lmer

All,
 
I'm using lmer for some repeated measures data and have specified 
the contrasts for a time factor such that say time 3 is the base.   This
works fine.  However, when 
I next use the subset argument to remove the last two time values, the
output indicates that
the specified contrast is not maintained (see below).   I can solve this
by creating a new dataframe
for the subset of interest and redefining the constrasts, but I was
wondering if there is a direct method that
allows me to continue w/ the subset argument?  (perhaps via supplying a
contrast argument to lmer 
directly, but this doesn't seem possible based on the defintion of this
argument in model.matrix.default).
 
Thanks,
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) 
 
### specify the contrast as time 3:
contrasts(dat.new$time) <- contr.treatment(6, base=3)     
dimnames(contrasts(dat.new$time))[[1]] <-
as.character(levels(dat.new$time))    
dimnames(contrasts(dat.new$time))[[2]] <-
as.character(levels(dat.new$time)[-3])
 
fm1 <- lmer(z ~ drug + time + (1 | Patient), data = dat.new )
Fixed effects:
             Estimate Std. Error  t value
(Intercept) -0.182774   0.464014 -0.39390
drugP       -0.281103   0.352309 -0.79789
timeTime-1   0.150505   0.606462  0.24817
timeTime-2   0.612016   0.606462  1.00916
timeTime-4   0.775342   0.606462  1.27847
timeTime-5   0.093741   0.606462  0.15457
timeTime-6   0.452442   0.606462  0.74604
 
## time 3 is the base as specified

fm2 <-  lmer(z ~ drug + time + (1 | Patient), data = dat.new, 
subset = dat.new$time !="Time-6" & dat.new$time != "Time-5")

Fixed effects:
             Estimate Std. Error  t value
(Intercept)  0.052975   0.500675  0.10581
drugP       -0.451593   0.447818 -1.00843
timeTime-2   0.461511   0.633310  0.72873
timeTime-3  -0.150505   0.633310 -0.23765
timeTime-4   0.624837   0.633310  0.98662
 
### time 3 no longer the base; was expecting to see the fixed effects
for time-1, time-2, and time-4, w/ Intercept 
### representing time-3
 
 

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All,
 
I'm using lmer for some repeated measures data and have specified 
the contrasts for a time factor such that say time 3 is the base.

works fine.  However, when
I next use the subset argument to remove the last two time values, the

output indicates that
the specified contrast is not maintained (see below).   I can solve

by creating a new dataframe
for the subset of interest and redefining the constrasts, but I was 
wondering if there is a direct method that allows me to continue w/ 
the subset argument?  (perhaps via supplying a contrast argument to 
lmer directly, but this doesn't seem possible based on the defintion 
of this argument in model.matrix.default).
 
Thanks,
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)
 
### specify the contrast as time 3:
contrasts(dat.new$time) <- contr.treatment(6, base=3)     
dimnames(contrasts(dat.new$time))[[1]] <-
as.character(levels(dat.new$time))    
dimnames(contrasts(dat.new$time))[[2]] <-
as.character(levels(dat.new$time)[-3])
 
fm1 <- lmer(z ~ drug + time + (1 | Patient), data = dat.new ) Fixed 
effects:
             Estimate Std. Error  t value
(Intercept) -0.182774   0.464014 -0.39390
drugP       -0.281103   0.352309 -0.79789
timeTime-1   0.150505   0.606462  0.24817
timeTime-2   0.612016   0.606462  1.00916
timeTime-4   0.775342   0.606462  1.27847
timeTime-5   0.093741   0.606462  0.15457
timeTime-6   0.452442   0.606462  0.74604
 
## time 3 is the base as specified

fm2 <-  lmer(z ~ drug + time + (1 | Patient), data = dat.new, subset =

dat.new$time !="Time-6" & dat.new$time != "Time-5")

Fixed effects:
             Estimate Std. Error  t value
(Intercept)  0.052975   0.500675  0.10581
drugP       -0.451593   0.447818 -1.00843
timeTime-2   0.461511   0.633310  0.72873
timeTime-3  -0.150505   0.633310 -0.23765
timeTime-4   0.624837   0.633310  0.98662
 
### time 3 no longer the base; was expecting to see the fixed effects 
for time-1, time-2, and time-4, w/ Intercept ### representing time-3
 
 

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