Message-ID: <1341935813289-4636009.post@n4.nabble.com>
Date: 2012-07-10T15:56:53Z
From: Ariel
Subject: multiple comparisons with generalised least squares
In-Reply-To: <1338909741362-4632412.post@n4.nabble.com>
racmar wrote
>
> I have also been searching various forums and books to see if there are
> any methods I could use and have only found people, such as yourself,
> asking the same question.
>
I was looking into this recently, as well, and found that the problem has to
do with building the model.matrix/terms/model.frame for gls objects when
using the glht function. I ended up creating three gls-specific functions
and was able to get estimates/confidence intervals for the toy example
below. You may find these functions useful (under the caveat that I only
checked that I got estimates and not that the estimates were correct ;) ).
Ariel
Example:
library(nlme)
Orthodont$fage <- factor(Orthodont$age)
#toy example with Orthodont data using age as a factor
fitgls <- gls( distance ~ fage, data=Orthodont,
weights = varIdent(form =~1|fage))
library(multcomp)
#notice the error about the model.matrix for gls objects when using glht
confint( glht (fitgls, mcp(fage="Tukey") ))
#create model.frame, terms, and model.matrix functions specifically for gls
objects
model.matrix.gls <- function(object, ...)
model.matrix(terms(object), data = getData(object), ...)
model.frame.gls <- function(object, ...)
model.frame(formula(object), data = getData(object), ...)
terms.gls <- function(object, ...)
terms(model.frame(object),...)
#now run glht again
confint( glht( fitgls, mcp(fage="Tukey") ))
--
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