[R-sig-ME] [ADMB Users] Anova table for glmm.admb objects
John Fox
jfox at mcmaster.ca
Wed Mar 28 00:19:05 CEST 2012
Dear Ben and Thomas,
As a brief addendum to Ben's helpful message, Anova.mer() in the development version of the car package on CRAN, which requires the development version of the pbkrtest package, can optionally compute F-tests for linear mixed models fit by REML, using Kenward-Roger df. The implementation may change before the current development version of car is released to CRAN.
Best,
John
On Tue, 27 Mar 2012 17:42:03 -0400
Ben Bolker <bbolker at gmail.com> wrote:
> A couple of things.
>
> (1) can you update.packages() or re-install R2admb and see if that
> helps with the R2admb/dat_write problem?
>
> (2) I would like to recant the Bolker et al decision tree somewhat.
> At the time I wrote it, I was somewhat confused (!!!!) about the
> distinction between the two difficulties with inference in the GLMM
> situation.
>
> * model comparisons are better than curvature-based approaches
> * approaches that allow for finite-sample effects are better than
> asymptotic approaches
> * there are two different kinds of finite size issues, one applying
> more to LMMs (the residual variance parameter used to scale the
> likelihood is estimated with uncertainty, hence we get an F statistic
> for the null hypothesis) and the other to GLM(M)s (the 'numerator' of
> the likelihood itself is only asymptotically normal) -- this is
> detailed a little more carefully at http://glmm.wikidot.com/faq (search
> for "degrees of freedom"
>
> When we wrote the TREE paper I thought it might be OK to use the
> classical experimental design 'denominator df' to correct for
> finite-size samples, but I'm no longer sure this is a good idea. In any
> case, car::Anova(glmerfit) gives Wald *CHI-SQUARE* tests (not F tests),
> so there's no advantage over drop1() except for computational speed.
>
> Hope that helps.
>
> Ben Bolker
>
>
>
> On 12-03-27 12:29 PM, Thomas Merkling wrote:
> > Dear all,
> >
> > I'm a bit confused about last comments from Ben Bolker.
> > I read Bolker et al., 2009 TREE and what I remembered is that it was
> > advised to use Wald tests instead of LRT whent testing for fixed effects
> > (and the contrary when testing for random effects). Hence, I'm surprised
> > that Ben just said the contrary: is it just true for glmmADMB or for any
> > packages ?
> >
> > If we want to use more accurate approaches, but if possible not MCMC
> > techniques, are there any possibilities with glmmADMB ?
> >
> > I tried to install glmmADMB_0.7.2.10 from bolker-mcmaster repository,
> > but I got the following error message:
> >
> > Installation d(es) package(s) dans ‘C:/Users/thomas
> > merkling/Documents/R/win-library/2.14’
> > (car ‘lib’ n'est pas spécifié)
> > * installing *source* package 'glmmADMB' ...
> > ** R
> > ** data
> > ** moving datasets to lazyload DB
> >
> > Error : l'objet 'dat_write' n'est pas exporté par 'namespace:R2admb'
> > ERROR: lazydata failed for package 'glmmADMB'
> >
> > * removing 'C:/Users/thomas merkling/Documents/R/win-library/2.14/glmmADMB'
> > * restoring previous 'C:/Users/thomas
> > merkling/Documents/R/win-library/2.14/glmmADMB'
> >
> >
> > Thanks in advance !
> > Thomas
> >
> >
> > Le 26/03/2012 18:12, Ben Bolker a écrit :
> >> On 12-03-26 10:37 AM, Paula Rosewarne wrote:
> >>> Dear All,
> >>>
> >>> I came across this posting (below) on a different list- how to get an
> >>> Anova table from glmm.admb model objects- but I cannot get the
> >>> car::Anova function to work for my model, or for the owl example I
> >>> worked through from the glmmadmb package help notes, so I am guessing
> >>> my code is wrong
> >>>
> >>> When I tried it with the owl example I get the following message, the
> >>> same as when I try for my model:
> >>>
> >>>> car::Anova(fit_zipoiss)
> >>> Error in data.frame(df, teststat, p) : arguments imply differing
> >>> number of rows: 5, 6 In addition: Warning message: In Ops.factor(1,
> >>> Nest) : | not meaningful for factors
> >>>
> >>>
> >>>
> >>> (I am using glmm.admb v0.7.2.4)
> >>>
> >>>
> >>>
> >>> Please could you advise, many thanks,
> >>>
> >>> Paula
> >>>
> >> [cross-posted to ADMB users and r-sig-mixed because I didn't want to
> >> write it twice]
> >>
> >> Before I answer the question I want to strongly caution people about
> >> using the Anova() (Wald) tests on glmmADMB output. I am generally of the
> >> "give people the tools, let them do what they want" [in other words
> >> "give them enough rope"] philosophy (which is why I tweaked glmmADMB to
> >> allow car::Anova() to work), but Wald tests are the most approximate
> >> approach to model comparison and inference. For vanilla (non-mixed)
> >> linear models they are identical to standard marginal F tests, but for
> >> mixed/generalized/zero-inflated models they are sometimes very poor
> >> approximations. Using anova() on alternative models instead gives a
> >> likelihood ratio test, which is still approximate but is generally much
> >> better (it relies on the normality of the likelihood itself, rather than
> >> on the normality of the sampling distribution of the parameters). It is
> >> a bit tedious to use in glmmADMB at the moment because I haven't got the
> >> drop1() functionality working yet, but it should be much more reliable.
> >> Even that is not perfect, though, because it does depend on the
> >> approximate normality of the likelihood estimate; MCMC and parametric
> >> bootstrap approaches are more accurate.
> >>
> >> You need at least version 0.7.2.9. I am currently struggling to get
> >> the newest version to build properly on r-forge; in the meantime, below
> >> is a helper function to check which versions are available where. You
> >> may want to use the optional argument type="source" (as documented at
> >> http://glmmadmb.r-forge.r-project.org) ...
> >>
> >> In the meantime I've put 0.7.2.10 (source only, use type="source") at
> >> the bolker-mcmaster repository and on the alternative r-forge location
> >> (where it should show up within 24 hours).
> >>
> >> ## helper function to check availability
> >> favail <- function(repos="r-forge.r-project.org",
> >> pkg="glmmADMB",
> >> ...) {
> >> hdr <- "http://"
> >> if (!substr(repos,1,8)==hdr) repos <- paste(hdr,repos,sep="")
> >> a <- available.packages(contriburl=contrib.url(repos),...)
> >> if (length(grep(pkg,rownames(a)))==0)
> >> stop(sprintf("%s unavailable at repos %s",pkg,repos))
> >> a[pkg,"Version"]
> >> }
> >>
> >> favail() ## unavailable
> >> favail("www.math.mcmaster.ca/bolker/R") ## 0.7.2.10
> >> favail("glmmadmb.r-forge.r-project.org/repos") ## 0.6.4
> >>
> >>>
> >>> From the r-sig-mixed-models list: Le 20/03/2012 22:43, Ben Bolker a
> >>> écrit : On 12-03-20 02:32 PM,
> >>>> Thomas Merkling wrote:
> >>>>>>> Dear Ben and other list members,
> >>>>>>>
> >>>>>>> - Is there any way to produce a Anova/deviance table for a
> >>>>>>> model fitted with glmmADMB ? I used the Anova() function
> >>>>>>> from the car library for glmer models, but it does not seem
> >>>>>>> to work with glmmadmb (I'm using glmmADMB 0.7) and I would
> >>>>>>> like only one p-value for each term and interaction and NOT
> >>>>>>> one p-value for each level of the interaction.
> >>> Ben's reply:
> >>>> car::Anova() should work now -- I had to add a model.frame() and a
> >>>> df.residual() method for glmmadmb objects. (The df.residual number
> >>>> may be a little dodgy -- I'm not sure I counted the parameters
> >>>> right -- but I don't think it's actually used for much by default,
> >>>> cause you get Wald chi-square tests)
> >>>
> >>>
> >>>
> >>> Paula Rosewarne, PhD researcher, Faculty of Biological Sciences
> >>> Manton Building 8.17 Clarendon Way University of Leeds LS2 9JT UK
> >>>
> >>> Email: bspjr at leeds.ac.uk<mailto:bspjr at leeds.ac.uk>
> >>> _______________________________________________ Users mailing list
> >>> Users at admb-project.org
> >>> http://lists.admb-project.org/mailman/listinfo/users
> >>
> >
> > --
> > ****NEW ADDRESS AND PHONE NUMBER ****
> >
> > Thomas Merkling, Doctorant (PhD Student)
> > Web Page <http://www.edb.ups-tlse.fr/Merkling-Thomas.html>
> >
> > Laboratoire "Evolution et Diversité Biologique" -EDB
> > UMR 5174 - bât 4R1 - bureau 33 RDC
> >
> > Université Paul Sabatier Toulouse 3
> > 118, route de Narbonne
> > 31062 TOULOUSE Cedex O9, FRANCE
> >
> > Tél: 33 5-61-55-67-56
> > Fax: 33 5-61-55-73-27
>
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