[R-sig-ME] MCMCglmm Poisson with an offset term and splines

[Matthew]

Hi Dani,


Redo the prior specification from scratch (i.e., overwrite the entire 
`prior` object). The original code creates an unecessary/undefined 
element in the prior list.


Matthew

****************************************************
Matthew E. Wolak, Ph.D.
Assistant Professor
Department of Biological Sciences
Auburn University
306 Funchess Hall
Auburn, AL 36849, USA
Email: matthew.wolak at auburn.edu

On 22/09/17 12:17, dani wrote:
>
> just a correction, the code prior$B$V[k,k]<-1e-8 works but the model 
> provides this error
>
>
> Error in MCMCglmm(y ~ x1 + x2 + X8 + x9 +x10 +  :
>   prior list should contain elements R, G, and/or B only
>
>
> Sent from Outlook <http://aka.ms/weboutlook>
>
>
> ------------------------------------------------------------------------
> *From:* Matthew <mew0099 at auburn.edu>
> *Sent:* Friday, September 22, 2017 10:10 AM
> *To:* dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org
> *Subject:* Re: [R-sig-ME] MCMCglmm Poisson with an offset term and 
> splines
> Hi Dani,
>
> Jarrod probably meant
>
> prior$B$mu[k]<-1 # assuming the offset term is last
> prior$B$V[k,k]<-1e-8
>
> Instead of:
>
> prior$mu[k]<-1 # assuming the offset term is last
> prior$B[k,k]<-1e-8
>
>
> Sincerely,
> Matthew
>
> ****************************************************
> Matthew E. Wolak, Ph.D.
> Assistant Professor
> Department of Biological Sciences
> Auburn University
> 306 Funchess Hall
> Auburn, AL 36849, USA
> Email: matthew.wolak at auburn.edu
>
> On 22/09/17 12:01, dani wrote:
> > Hi Jarrod,
> >
> >
> > Thank you so much for your prompt and helpful response!
> >
> > I ran the code you sent me for the prior, but I am getting the 
> following error:
> >
> > Error in prior$B[k, k] <- 1e-08 :
> >    incorrect number of subscripts on matrix
> >
> >
> > Here is what I get for prior:
> >> prior
> > $B
> > $B$V
> >         [,1]  [,2]  [,3]  [,4]  [,5]  [,6]  [,7] [,8]  [,9] [,10] [,11]
> >   [1,] 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [2,] 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [3,] 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [4,] 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [5,] 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [6,] 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00
> >   [7,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00
> >   [8,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00
> >   [9,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00
> > [10,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00
> > [11,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08
> >
> > $B$mu
> >   [1] 0 0 0 0 0 0 0 0 0 0 0
> >
> >
> > $R
> > $R$V
> > [1] 1
> >
> > $R$nu
> > [1] 0
> >
> >
> > $G
> > $G$G1
> > $G$G1$V
> > [1] 1
> >
> > $G$G1$nu
> > [1] 0
> >
> >
> > $G$G2
> > $G$G2$V
> > [1] 1
> >
> > $G$G2$nu
> > [1] 0
> >
> >
> > $G$G3
> > $G$G3$V
> > [1] 1
> >
> > $G$G3$nu
> > [1] 0
> >
> >
> >
> > $mu
> >   [1] NA NA NA NA NA NA NA NA NA NA  1
> >
> >
> >
> > I am not sure what to do next. Any help would be very appreciated!
> >
> > Best regards,
> >
> > N-M
> >
> >
> >
> > Sent from Outlook<http://aka.ms/weboutlook>
> >
> >
> > ________________________________
> > From: Jarrod Hadfield <j.hadfield at ed.ac.uk>
> > Sent: Thursday, September 21, 2017 9:55 PM
> > To: dani; r-sig-mixed-models at r-project.org
> > Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
> >
> > Hi,
> >
> > The model looks OK as far as can be assessed without knowing the data.
> > For the offset term you need to hold the associated coefficient at 1 by
> > placing a strong prior on it. If  you want everything else to have the
> > default prior then use:
> >
> > k<-11 # number of fixed effects
> >
> > prior<-list(B=list(V=diag(k)*1e8, mu=rep(0,k)),
> >               R=list(V=1, nu=0),
> >               G=list(G1=list(V=1, nu=0),
> >                      G2=list(V=1, nu=0),
> >                      G3=list(V=1, nu=0)))
> >
> > prior$mu[k]<-1 # assuming the offset term is last
> > prior$B[k,k]<-1e-8
> >
> > The interpretation of the offset is simply the coefficient is assumed to
> > be one and that the rate at which events occur is constant.
> >
> > Cheers,
> >
> > Jarrod
> >
> >
> >
> >
> > On 22/09/2017 01:52, dani wrote:
> >> Hello everyone,
> >>
> >> I have a Poisson model with an offset term that involves repeated 
> observations nested into two cross-classified groups.
> >>
> >> The model includes
> >> - four categorical variables
> >> - 6 continuous variables (for one of them I would like to include a 
> smoother)
> >> - the offset=log(duration)
> >>
> >> I first used the spl2 function to create the fixed ((x6numspline1) 
> and random terms (x6numspline2) for the smoother. I added the random 
> smoother term to the other two random intercepts (for student ID and 
> classroom) that I have (which are cross-classified).
> >>
> >> My question is: Do you find my model sound? Before I study the 
> priors, I just wanted to run a default model - is my inclusion of an 
> offset ok? Also, given that the observations are repeated and nested 
> into both Student ID and classroom, I am not sure how to specify the 
> variance structure in MCMCglmm (beginner here:))
> >>
> >> mc_spl0 <- MCMCglmm(number_events ~ 
> x1cat+x2cat+x8cat+x9cat+x3num+x4num+x5num+x6numspline1+x7num+x8num+log(duration),
> >>                       random =~ ID+class+idv(x6numspline2),
> >>                       data   = newdat,
> >>                       family = "poisson",
> >>                       thin   = 100,
> >>                       burnin = 10000,
> >>                       nitt   = 150000,
> >>                       saveX=TRUE, saveZ=TRUE, saveXL=TRUE, pr=TRUE, 
> pl=TRUE)
> >>
> >> In addition, I am not sure what to make of the results for the 
> offset term (included as a covariate in the model) in the output - how 
> should I discuss them?
> >>
> >> Thank you all so much!
> >> Best regards,
> >> N-M.
> >> <http://aka.ms/weboutlook>
> >>
> >>         [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-mixed-models at r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> > --
> > The University of Edinburgh is a charitable body, registered in
> > Scotland, with registration number SC005336.
> >
> >
> >        [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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