[R] multcomp and lme
Torsten Hothorn
Torsten.Hothorn at rzmail.uni-erlangen.de
Tue May 6 12:35:32 CEST 2003
> 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))
> Thank you very much.
>
> Peter B.
_______________________________________________________________________
| |
| Dipl.-Stat. Torsten Hothorn |
| Institut fuer Medizininformatik, Biometrie und Epidemiologie |
| Waldstrasse 6, D-91054 Erlangen, Deutschland |
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| Email: Torsten.Hothorn at rzmail.uni-erlangen.de |
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