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>
MCMCglmm Poisson with an offset term and splines
9 messages · Jarrod Hadfield, dani, Matthew +1 more
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.
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
$mu
[1] NA NA NA NA NA NA NA NA NA NA 1
I am not sure what to do next. Any help would be very appreciated!
Best regards,
N-M
Sent from Outlook<http://aka.ms/weboutlook>
From: Jarrod Hadfield <j.hadfield at ed.ac.uk>
Sent: Thursday, September 21, 2017 9:55 PM
To: dani; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Sent: Thursday, September 21, 2017 9:55 PM
To: dani; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Hi,
The model looks OK as far as can be assessed without knowing the data.
For the offset term you need to hold the associated coefficient at 1 by
placing a strong prior on it. If you want everything else to have the
default prior then use:
k<-11 # number of fixed effects
prior<-list(B=list(V=diag(k)*1e8, mu=rep(0,k)),
R=list(V=1, nu=0),
G=list(G1=list(V=1, nu=0),
G2=list(V=1, nu=0),
G3=list(V=1, nu=0)))
prior$mu[k]<-1 # assuming the offset term is last
prior$B[k,k]<-1e-8
The interpretation of the offset is simply the coefficient is assumed to
be one and that the rate at which events occur is constant.
Cheers,
Jarrod
On 22/09/2017 01:52, dani wrote:
> Hello everyone,
>
> I have a Poisson model with an offset term that involves repeated observations nested into two cross-classified groups.
>
> The model includes
> - four categorical variables
> - 6 continuous variables (for one of them I would like to include a smoother)
> - the offset=log(duration)
>
> I first used the spl2 function to create the fixed ((x6numspline1) and random terms (x6numspline2) for the smoother. I added the random smoother term to the other two random intercepts (for student ID and classroom) that I have (which are cross-classified).
>
> My question is: Do you find my model sound? Before I study the priors, I just wanted to run a default model - is my inclusion of an offset ok? Also, given that the observations are repeated and nested into both Student ID and classroom, I am not sure how to specify the variance structure in MCMCglmm (beginner here:))
>
> mc_spl0 <- MCMCglmm(number_events ~ x1cat+x2cat+x8cat+x9cat+x3num+x4num+x5num+x6numspline1+x7num+x8num+log(duration),
> random =~ ID+class+idv(x6numspline2),
> data = newdat,
> family = "poisson",
> thin = 100,
> burnin = 10000,
> nitt = 150000,
> saveX=TRUE, saveZ=TRUE, saveXL=TRUE, pr=TRUE, pl=TRUE)
>
> In addition, I am not sure what to make of the results for the offset term (included as a covariate in the model) in the output - how should I discuss them?
>
> Thank you all so much!
> Best regards,
> N-M.
> <http://aka.ms/weboutlook>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
Hi Dani, Jarrod probably meant prior$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
Hi Matt, Thank you so much! I did try that code, as well, with the same result. Not sure what to do next:) Best regards! 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
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
just a correction, the code prior$B$V[k,k]<-1e-8 works but the model provides this error Error in MCMCglmm(y ~ x1 + x2 + X8 + x9 +x10 + : prior list should contain elements R, G, and/or B only Sent from Outlook<http://aka.ms/weboutlook>
From: Matthew <mew0099 at auburn.edu>
Sent: Friday, September 22, 2017 10:10 AM
To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Sent: Friday, September 22, 2017 10:10 AM
To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Hi Dani, Jarrod probably meant prior$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
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
Hi again, Thanks! It looks like it is working. This is like V looks like:
prior$B$V
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [1,] 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [2,] 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [3,] 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [4,] 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [5,] 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [6,] 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 [7,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 [8,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 [9,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 [10,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 [11,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e-08 However, when I run my model, I get this new error: fixed effect V prior is not positive definite Thanks! Sent from Outlook<http://aka.ms/weboutlook>
From: Matthew <mew0099 at auburn.edu>
Sent: Friday, September 22, 2017 10:20:45 AM
To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Sent: Friday, September 22, 2017 10:20:45 AM
To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines
Hi Dani, Redo the prior specification from scratch (i.e., overwrite the entire `prior` object). The original code creates an unecessary/undefined element in the prior list. Matthew **************************************************** Matthew E. Wolak, Ph.D. Assistant Professor Department of Biological Sciences Auburn University 306 Funchess Hall Auburn, AL 36849, USA Email: matthew.wolak at auburn.edu<mailto:matthew.wolak at auburn.edu> On 22/09/17 12:17, dani wrote: just a correction, the code prior$B$V[k,k]<-1e-8 works but the model provides this error Error in MCMCglmm(y ~ x1 + x2 + X8 + x9 +x10 + : prior list should contain elements R, G, and/or B only Sent from Outlook<http://aka.ms/weboutlook> ________________________________ From: Matthew <mew0099 at auburn.edu><mailto:mew0099 at auburn.edu> Sent: Friday, September 22, 2017 10:10 AM To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org> Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines Hi Dani, Jarrod probably meant prior$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$B[k,k]<-1e-8 Sincerely, Matthew **************************************************** Matthew E. Wolak, Ph.D. Assistant Professor Department of Biological Sciences Auburn University 306 Funchess Hall Auburn, AL 36849, USA Email: matthew.wolak at auburn.edu<mailto:matthew.wolak at auburn.edu> On 22/09/17 12:01, dani wrote: > Hi Jarrod, > > > Thank you so much for your prompt and helpful response! > > I ran the code you sent me for the prior, but I am getting the following error: > > Error in prior$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 > > > > $mu > [1] NA NA NA NA NA NA NA NA NA NA 1 > > > > I am not sure what to do next. Any help would be very appreciated! > > Best regards, > > N-M > > > > Sent from Outlook<http://aka.ms/weboutlook> > > > ________________________________ > From: Jarrod Hadfield <j.hadfield at ed.ac.uk><mailto:j.hadfield at ed.ac.uk> > Sent: Thursday, September 21, 2017 9:55 PM > To: dani; r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org> > Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines > > Hi, > > The model looks OK as far as can be assessed without knowing the data. > For the offset term you need to hold the associated coefficient at 1 by > placing a strong prior on it. If you want everything else to have the > default prior then use: > > k<-11 # number of fixed effects > > prior<-list(B=list(V=diag(k)*1e8, mu=rep(0,k)), > R=list(V=1, nu=0), > G=list(G1=list(V=1, nu=0), > G2=list(V=1, nu=0), > G3=list(V=1, nu=0))) > > prior$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<mailto: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<mailto:R-sig-mixed-models at r-project.org> mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
I suspect that the broad range of the prior variances (from 1e8 to 1e-8) has led to an underflow error. Try setting the prior variances to 1e4 for all but the offset element and 1e-4 for the offset element ... Just a quick comment: this is why it can be helpful to provide a minimal reproducible example (you don't necessarily have to give us all of your data: see https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example). Debugging one step at a time can be frustrating for all concerned ...
On Fri, Sep 22, 2017 at 1:34 PM, dani <orchidn at live.com> wrote:
Hi again, Thanks! It looks like it is working. This is like V looks like:
prior$B$V
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [1,] 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [2,] 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [3,] 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [4,] 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [5,] 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 [6,] 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 0e+00 [7,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 0e+00 [8,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 0e+00 [9,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 0e+00 [10,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e+08 0e+00 [11,] 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 1e-08 However, when I run my model, I get this new error: fixed effect V prior is not positive definite Thanks! Sent from Outlook<http://aka.ms/weboutlook>
________________________________ From: Matthew <mew0099 at auburn.edu> Sent: Friday, September 22, 2017 10:20:45 AM To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines Hi Dani, Redo the prior specification from scratch (i.e., overwrite the entire `prior` object). The original code creates an unecessary/undefined element in the prior list. Matthew **************************************************** Matthew E. Wolak, Ph.D. Assistant Professor Department of Biological Sciences Auburn University 306 Funchess Hall Auburn, AL 36849, USA Email: matthew.wolak at auburn.edu<mailto:matthew.wolak at auburn.edu> On 22/09/17 12:17, dani wrote: just a correction, the code prior$B$V[k,k]<-1e-8 works but the model provides this error Error in MCMCglmm(y ~ x1 + x2 + X8 + x9 +x10 + : prior list should contain elements R, G, and/or B only Sent from Outlook<http://aka.ms/weboutlook> ________________________________ From: Matthew <mew0099 at auburn.edu><mailto:mew0099 at auburn.edu> Sent: Friday, September 22, 2017 10:10 AM To: dani; Jarrod Hadfield; r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org> Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines Hi Dani, Jarrod probably meant prior$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$B[k,k]<-1e-8 Sincerely, Matthew **************************************************** Matthew E. Wolak, Ph.D. Assistant Professor Department of Biological Sciences Auburn University 306 Funchess Hall Auburn, AL 36849, USA Email: matthew.wolak at auburn.edu<mailto:matthew.wolak at auburn.edu> On 22/09/17 12:01, dani wrote: Hi Jarrod, Thank you so much for your prompt and helpful response! I ran the code you sent me for the prior, but I am getting the following error: Error in prior$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 $mu [1] NA NA NA NA NA NA NA NA NA NA 1 I am not sure what to do next. Any help would be very appreciated! Best regards, N-M Sent from Outlook<http://aka.ms/weboutlook> ________________________________ From: Jarrod Hadfield <j.hadfield at ed.ac.uk><mailto:j.hadfield at ed.ac.uk> Sent: Thursday, September 21, 2017 9:55 PM To: dani; r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org> Subject: Re: [R-sig-ME] MCMCglmm Poisson with an offset term and splines Hi, The model looks OK as far as can be assessed without knowing the data. For the offset term you need to hold the associated coefficient at 1 by placing a strong prior on it. If you want everything else to have the default prior then use: k<-11 # number of fixed effects prior<-list(B=list(V=diag(k)*1e8, mu=rep(0,k)), R=list(V=1, nu=0), G=list(G1=list(V=1, nu=0), G2=list(V=1, nu=0), G3=list(V=1, nu=0))) prior$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<mailto: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<mailto:R-sig-mixed-models at r-project.org> mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models [[alternative HTML version deleted]] _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models