Hi,
I would like to derive p-values for pair-wise comparison (Tukey's) of
effects when the response is a count.
I am trying a test case where y ~ Po( lambda(x) ). x has three
levels : A, B and C with lambda(x) = 10, 20 and 20 respectively.
Hence, p-values for the contrast C - B should distribute uniformally.
I have implemented this test case as below but do not get uniform
distribution of those p-values, rather high values (close to 1). Is my
code correct? The problem could be due to the normal approximation but
I have also tried with larger sample sizes (n=1e4) and still get it.
Is there an issue in using multcomp for count data? My final real case
will be with quasipoisson data.
Thanks for your help,
Julien
seed(0)
pvals = t(
sapply(
1:100,
function(i){
x = factor(sample( c("A", "B", "C"), 1000, replace=TRUE ))
means = c(A=10, B=20, C=20)
y = rpois(length(x), lambda=means[x])
fit = glm(y ~ x , family=poisson() )
summary( glht(fit, linfct = mcp(x = "Tukey") ) )$test
$pvalues
}
)
)
hist(pvals[,3], breaks=30)
> Julien Gagneur
> Computational Scientist
> Steinmetz lab
> Tel: +49-(0)6221-387-8114
> Fax: +49-(0)6221-387-8518
> Email: julien.gagn...@embl.de
>
> Room V205
> EMBL
> Meyerhofstrasse 1
> D-69117 Heidelberg
> Germany
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