Dear all,

I have to analyse the outcome of an experiment of this kind:
subjects (1-20) assigned to a treatment with two levels: A and B (ten to A
and ten to B).
the response variable (resp) has been measured twice, however the time
interval between the two measurement and the biological meaning of the
experiment allow me to consider the two repeated measures as not temporally
auto correlated. Therefore the only random effect would be subject, and I’m
using the two measures as blocking factors called "date".
The design of the experiment is as follow:

treatment         A    B
date            1   10  10
                    2   10  10

What I’m interested to is the mean value of resp.
after the model selection procedure i came up with the best following model:

model<-lme(resp~treatemt*date, random=~1|subject,data)

I'm happy with this and all make sense, but now i what to make a pairwise
comparison.
To do so  i'm trying this way:

K<-cbind(0,diag(length(fixef(model))-1)
rownames(K)<-names(fixef(model))[-1]
test<-glht(model,linfct=K)

which gives:

treatmentB==0
date2==0
treatmentB:date2==0

but this tests if the differences between the estimated value of the fixed
effects are equal to zero, and, correct me if i'm wrong, it gives the same
kind of information of the lme summary table.
what i actually want is to know if the difference between all the possible
pair combinations are significant, something that look like the outcome of
the same TukeyHSD()
which would be:

treatmentAdate1=treatmentBdate1
treatmentAdate2=treatmentBdate2
treatmentAdate1=treatmentBdate2
treatmentAdate1=treatmentAdate2
treatmentBdate1=treatmentAdate2
treatmentBdate1=treatmentBdate2

I’ve been looking for but i couldn't find anything helpful. Any suggestion?
And an another question which maybe not appropriate for this list. When it
comes to present the results is it correct make a box plot of the predicted
value of the model?

ps. as i moving the first steps in either statistical modelling and in this
list, please accept my  naiveness, and of course i'm very open to any kind
of corrections..

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