This is because pairwise.student.t and TukeyHSD use differents estimates for
error term. TukeyHSD use the parameters covariance matrix and t use sample
variance. In this case a treatment with only one value doesn't have sample
variance but has a estimated standard error in a covariance matrix. The
lines below will illustrate the point:
# toy data
da <- data.frame(A=factor(rep(c("a","b","c"), c(1,5,7))))
da$y <- rnorm(da$A)
# sample variance
tapply(da$y, da$A, var)
pairwise.t.test(da$y, da$A, p.adj="none") # problem!
# model and covariance matriz
m0 <- aov(y~A, da)
vcov(m0)
TukeyHSD(m0) # no problem!
Walmes.
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..ooo0
...................................................................................................
..(....)... 0ooo... Walmes Zeviani
...\..(.....(.....)... Master in Statistics and Agricultural
Experimentation
....\_)..... )../.... walmeszevi...@hotmail.com, Lavras - MG, Brasil
............
(_/............................................................................................
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