[R-sig-ME] lmer and post-hoc testing
Thierry.ONKELINX at inbo.be
Tue Jan 11 09:54:30 CET 2011
Try converting Arena to a factor in your data.frame. And then run the
Your.data.frame$Arena <- factor(Your.data.frame$Arena)
model1<-lmer(y~Arena+SL+(1|FishID), family=binomial, data =
factor(Arena) and Arena are two different variables. That's what causing
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Research Institute for Nature and Forest
team Biometrics & Quality Assurance
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
~ John Tukey
> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces at r-project.org
> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens
> SHONA MARY LESLIE
> Verzonden: maandag 10 januari 2011 17:54
> Aan: r-sig-mixed-models at r-project.org
> Onderwerp: [R-sig-ME] lmer and post-hoc testing
> Hi there,
> I am investigating habitat preference in 9-spined
> sticklebacks using 4 experimental arenas (each fish spent
> same time in each arena) and want to know whether the time in
> the shallow area was different between arenas.
> I carried out a generalised linear mixed model (using lmer),
> putting in the fish ID as a random effect, and the
> distribution as binomial (since it's proportion data); as follows...
> > model1<-lmer(y~factor(Arena)+SL+(1|FishID), family=binomial)
> > summary(model1)
> This worked but I can't work out how to run a Tukey test, to
> see which arenas were different. I have tried... (with error
> message underneath)
> > TukeyHSD(model1)
> Error in UseMethod("TukeyHSD") :
> no applicable method for 'TukeyHSD' applied to an object of
> class "mer"
> > summary(glht(model1,linfct=mcp(Arena="Tukey")))
> Error in summary(glht(model1, linfct = mcp(Arena = "Tukey"))) :
> error in evaluating the argument 'object' in selecting a
> method for function 'summary'
> > glht(model1, linfct=mcp(Arena="Tukey"))
> Error in mcp2matrix(model, linfct = linfct) :
> Variable(s) 'Arena' have been specified in 'linfct' but
> cannot be found in 'model'!
> > glht(model1, linfct=mcp(factor(Arena)="Tukey")
> Error: unexpected '=' in "glht(model1, linfct=mcp(factor(Arena)="
> I have read some of the R help archives and it has been
> pointed out that Tukey may or may not work with lmer (I
> downloaded the newest version and still no luck). Any ideas?
> If Tukey won't work, are there others that might?
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