I suppose that multcomp in R and multicomp in S-Plus are related
not really, there are huge differences.
and it
appears that it is possible to use multicomp with lme in S-Plus given
the
following correspondence on s-news
sally.rodriguez at philips.com 12:57 p.m. 24/04/03 -0400 7
[S] LME
summary
and multicomp.default()
Is it possible to use multicomp with lme in R and if so what is the
syntax
from a simple readily available example such as the data frame HR in the
library SASmixed?.
it is possible, yes, but you have to do some extra work. The package
offers two low-level functions `csimint' and `csimtest' which compute
adjusted p-values based on the estimated effects and their covariance
matrix. That means that you have to
1) compute the appropriate contrast matrix (maybe using `contrMat')
2) define the contrasts of the factor of interest (there is a section
in MASS on how to do it)
3) fit the model
4) and compute the covariance matrix via `vcov'
and you have everything you need to proceed. I attach a short example
using glm, lme should be along the same lines...
best,
Torsten
---------------------------------------------------------------------
library(multcomp)
set.seed(290875)
# a factor at three levels
group <- factor(c(rep(1,10), rep(2, 10), rep(3,10)))
# Williams contrasts
contrasts(group) <- mginv(contrMat(table(group), type="Will"))
# a binary response
z <- factor(rbinom(30, 1, 0.5))
# estimate the model
gmod <- glm( z ~ group, family=binomial(link = "logit"))
# exclude the intercept
summary(csimtest(coef(gmod)[2:3], vcov(gmod)[2:3,2:3],
cmatrix=diag(2), df=27))