Hi,
I have a fairly simple repeated measures-type data set I've been attempting
to analyze using the lme function in the nlme package. Repeated searches
here and other places lead me to believe I have specified my model
correctly.
However, I am having trouble with post-hoc tests. From what I gather, other
people are successfully using the glht function from the multcomp package to
perform post-hoc tests. I've tried multiple iterations, but can't seem to
get it to work. Here is (a subset of) what I have been trying. Any help
would be greatly appreciated:
> model.3<-lme(fixed=Totnum~Wk*Pop, random=~1|nUID, data=nona)
#Wk has 6 levels, 0-5; Pop has 2 levels; nUID is a unique ID given to each
individual (multiple individuals from each population were re-measured each
week)
> anova(model.3)
numDF denDF F-value p-value
(Intercept) 1 592 649.7753 <.0001
Week 5 592 302.9706 <.0001
Pop 1 222 70.7268 <.0001
Week:Pop 5 592 36.8576 <.0001
> summary(glht(model.3, linfct=mcp(Wk = "Tukey")))
Error in mcp2matrix(model, linfct = linfct) :
Variable(s) ‘Wk’ of class ‘integer’ is/are not contained as a factor in
‘model’.
> is.factor(Wk)
[1] FALSE
> Week<-factor(Wk)
> is.factor(Week)
[1] TRUE
> model.3<-lme(fixed=Totnum~Week*Pop, random=~1|nUID)
> summary(glht(model.3, linfct=mcp(Week = "Tukey")))
Error in contrMat(table(mf[[nm]]), type = types[pm]) :
less than two groups
Thanks,
Rob
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