[R-sig-ME] Comparison of crossed ranom effects: lmer vs. MCMCglmm

[Linus Holtermann]

Thanks Jarrod. 
Just to be on the safe side, MCMCglmm indeed fits two independent random effects in the "mcmc"-specification? The different results emerge because the MCMC-Approach treat the variance components as random variables that capture more of the skewness?  It is often claimed that mixed models fitted via Maximum Likelihood underestimate the random effect variance.


Best regards,


Linus Holtermann
Hamburgisches WeltWirtschaftsInstitut gemeinnützige GmbH (HWWI)
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________________________________________
Von: Jarrod Hadfield [j.hadfield at ed.ac.uk]
Gesendet: Montag, 19. Januar 2015 19:25
An: Linus Holtermann
Cc: r-sig-mixed-models at r-project.org
Betreff: Re: [R-sig-ME] Comparison of crossed ranom effects: lmer vs. MCMCglmm

Hi Linus,

The point estimates are almost identical if the posterior mode is used:

hist(mcmc$VCV[,"plate"], breaks=30)

abline(v=VarCorr(ml)[["plate"]][1], col="red")

The posterior mean (which is reported in the summary) is often not a
good measure of central tendency for variance components because of
the skew. Posterior modes have high Monte Carlo error though.

Cheers,

Jarrod




Quoting Linus Holtermann <holtermann at hwwi.org> on Mon, 19 Jan 2015
18:39:52 +0100:

> Hello,
>
> I read that lmer can handle independent (often labelled as crossed)
> random effets in mixed models. It seems to be possible with MCMCglmm
> as long as groups for the random effects are uniquely labelled. I
> use the "Penicllin" data in the lme4-package to compare both
> approaches:
>
> library(lme4)
> library(MCMCglmm)
>
> str(Penicillin)
> attach(Penicillin)
>
> ml <- lmer(diameter~ 1 + (1|plate)+ (1|sample))
> summary(ml)
>
> mcmc <- MCMCglmm(diameter~ 1, random=~ plate + sample,verbose=F,
> nitt=110000,burn=10000,thin=10,data=Penicillin)
> summary(mcmc)
>
> Why are the result for the plate-variance differ by a large amount?
> Is it because MCMCglmm applies Gibbs sampling? Or is MCMCglmm doing
> something else here, instead of fitting independent random effects?
>
>
> Best regards,
>
>
> Linus Holtermann
> Hamburgisches WeltWirtschaftsInstitut gemeinnützige GmbH (HWWI)
> Heimhuder Straße 71
> 20148 Hamburg
> Tel +49-(0)40-340576-336
> Fax+49-(0)40-340576-776
> Internet: www.hwwi.org
> Email: holtermann at hwwi.org
>
> Amtsgericht Hamburg HRB 94303
> Geschäftsführer: PD Dr. Christian Growitsch | Prof. Dr. Henning Vöpel
> Prokura: Dipl. Kauffrau Alexis Malchin
> Umsatzsteuer-ID: DE 241849425
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>


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