[R-sig-ME] HPDinterval MCMCglmm and using transformed variables in MCMCglmm

[Rebecca Ross]

Hi Jarrod,

Thank you for the quick reply.

I tried that one already and it hasnt made a difference (also I haven't closed down R since it worked last night). 

I guess...close R down and start again?!

Re logs - presumably I(x^2) is also not recognised (I had a go but the x2 term did not appear in the Sol output)?

Cheers,

Rebecca



________________________________________
From: Jarrod Hadfield [j.hadfield at ed.ac.uk]
Sent: Monday, July 12, 2010 11:30 AM
To: Rebecca Ross
Cc: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] HPDinterval MCMCglmm and using transformed variables in MCMCglmm

Dear Rebecca,

You probably need to load MCMCglmm (library(MCMCglmm)) or at least
load coda. At the moment the response needs to be logged externally:

my.data$ylog<-log(my.data$y)

but the next version will "fix" this.

Cheers,

Jarrod


On 12 Jul 2010, at 10:31, Rebecca Ross wrote:

> Dear ME users,
>
> Apologies if this is a naive question, I am new to using MCMC glmm.
> I have been working through the tutorial, using some of my own data,
> and I thought I had followed the steps correctly. The model I have
> been fitting is:
>
> AMstem3<-MCMCglmm(log(stem)~Dist_fr_A,random=~Block
> +animal,pedigree=Ped,data=SapRO,prior=prior1.3,
> family="gaussian")
> Briefly, I want to see how the Distance variable (continuous)
> affects stem weight, which I have log transformed as the raw data is
> heteroscedastic. Block is field block, and I am fitting the animal
> random effect to take into account different relatedness between
> individuals (I'm not at the moment trying to estimate Va).
>
> When I tried this model last night, I could get the 95% CIs using
> this function
> HPDinterval(AMstem3$Sol[,"Dist_fr_A"])
> HPDinterval(AMstem3$VCV)
>
> When I tried this morning, I get the following error message
> Error in function (classes, fdef, mtable)  :
>  unable to find an inherited method for function "HPDinterval", for
> signature "mcmc"
> Can anyone explain what  has gone wrong? I've tried changing the
> terms in the model, but that doesn't help, so I think I must have
> changed something in R elsewhere? Or else missing something
> completely obvious.
>
> Question 2: I dont think MCMCglmm is actually logging my stem
> variable because the fixed effect parameter estimate from the model
> above (AMstem3) are about a factor of 10 out from the fixed effect
> estimate from
> a similar model, fit in lme4, without the animal effect and very
> similar to the same model using the raw stem weight (see below). Do
> I need to specify the log transform differently?
>
> AMstem3c Dist_fr_A  posterior mode: -0.004236659
> versus:
> stem5a<-lme(log(stem)~Dist_fr_A,random=~1|
> Block,data=SapRO,na.action=na.omit)
> Fixed effect Estimate: Dist_fr_A   -0.0004442 (SE=0.00006136)
> and:
> stem5b<-lme(stem~Dist_fr_A,random=~1|
> Block,data=SapRO,na.action=na.omit)
> Fixed effect Estimate: Dist_fr_A   -0.004342 (SE=0.0006714)
>
> Thank you very much for your help,
>
> Rebecca Ross
> DPhil Candidate,
> University of Oxford.
>
>
>
>
>       [[alternative HTML version deleted]]
>
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>


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