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List:       r-sig-mixed-models
Subject:    Re: [R-sig-ME] MCMCglmm function
From:       Ben Bolker <bbolker () gmail ! com>
Date:       2016-08-01 18:48:15
Message-ID: 28473d2b-7593-8443-578f-cea26b2f9925 () gmail ! com
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  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
> 
> 
> 
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 

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