[R-sig-ME] MCMCglmm function

[Ben Bolker]

  Just a quick reminder: while I (a) answer a lot of the posts here and
(b) spend a lot of time encouraging people to post here rather than
e-mailing me privately, this is *not* my e-mail: "Dear list" or "Dear
kind and generous mixed model gurus" (or something like that) would be a
better salutation ...

  have you looked at the section on multinomial models (p. 95) in
vignette("CourseNotes",package="MCMCglmm") yet ... ?

  good luck,
   Ben Bolker

On 16-08-01 09:26 AM, Arianna Cecchetti wrote:
> Dear Prof. Bolker,
> 
> I am trying to find the best model to fit a set of data which are temporally correlated and which involve a factor response variable including three levels. I would like to test a GLMM and possibly compare it with a multinomial GEE.
> However, all the examples I found for GLMM using a factor as response variable are binomial and family options for the glmer function in R do not include multinomial. When I run it without specifying the family it automatically performs a LMM with a Gaussian distribution and besides not being sure it is a suitable option the output doesn’t show the levels of each explanatory factor variable.
> I found that the multinomial family is an option for the MCMCglmm function which also deals with temporal correlation, however when it comes to select the random effect I have a doubt and I am not sure I am understanding how to set it correctly. I have been reading the function help file in R and the paper “GLMMs in action” however I have still doubts.
> 
> The data I am using are temporally correlated at sequence level (i.e. all data are correlated within each sequence cluster) and I set this variable as random effect. Do all fixed variable need to be included at once in the random specification?
> 
> It didn’t seem so in one example, so I was trying the following code. However, it failed giving the error “unexpected input in model <- …” guessing there is a syntax error but I have not been able to detect it. I include a subset of the data.
> 
> trial <- read.csv(“swd.csv”, sep=”,” , header=T)
> trial$Dolphins.response=as.factor(trial$Dolphins.response)
> trial$Behaviour=as.factor(trial$Behaviour)
> trial$N.Sequence=as.factor(trial$N.Sequence)
> 
> model <- MCMCglmm(Dolphins.response~Species + Boat.placement + Behaviour + Calves + Group.size + N.Swimmers , random=~idh(N.Swimmers):N.Sequence, data=trial, family=“multinomial”,  verbose=FALSE)
> 
> 
> Any suggestion to get me on the right track is very much appreciated!
> 
> Thank you very much!
> 
> Best wishes,
> 
> Arianna
> 
> 
> 
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