AFAIK likelihood ratio tests are preferable, especially when you're
interested in testing several fixed-effects simultaneously. However,
since in GLMMs the likelihood cannot be calculated explicitly one
could wonder how does this affect LRTs.
Adaptive Gaussian quadrature is know to provide the best
approximation; however, taking into account the random-effects
structure in your model I doubt if it'd ever convergence in this year.
Thus, I think Laplace is the best you can have in a reasonable
computing time.
Regarding `method = "ML"' I think this refers to the linear mixed
model case where you also have the option for REML (the default).
I hope it helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Martin Henry H. Stevens" <hstevens at muohio.edu>
To: "R-Help" <r-help at stat.math.ethz.ch>
Sent: Friday, June 09, 2006 3:55 PM
Subject: [R] binomial lmer and fixed effects
> Hi Folks,
>
> I think I have searched exhaustively, including, of course R-help
> (D.
> Bates, S. Graves, and others) and but I remain uncertain about
> testing fixed effects with lmer(..., family=binomial).
>
> I gather that mcmcsamp does not work with Do we rely exclusively on
> z
> values of model parameters, or could we use anova() with likelihood
> ratios, AIC and BIC, with (or without) method="ML" (with
didn't seem
> right to me)?
>
> I also received an error using adaptive Gaussian quadrature (but not
> Laplacian approximations):
>
> > mod2 <- lmer(yb ~ reg*nutrient*amd +
> + (1|rack) + (1|status) +
> + (1|popu) + (1|popu:amd) +
> + (1|gen) + (1|gen:nutrient) + (1|gen:amd) +
> + (1|gen:nutrient:amd),
> + data=datnm, family=binomial, method="AGQ")
> Error in lmer(yb ~ reg * nutrient * amd + (1 | rack) + (1 | status)
> + :
> method = "AGQ" not yet implemented for supernodal representation
>
> I would really appreciate any and all thoughts or leads.
>
> Cheers,
> Hank Stevens
>
> > version
> _
> platform powerpc-apple-darwin8.6.0
> arch powerpc
> os darwin8.6.0
> system powerpc, darwin8.6.0
> status
> major 2
> minor 3.1
> year 2006
> month 06
> day 01
> svn rev 38247
> language R
> version.string Version 2.3.1 (2006-06-01)
> >
>
>
>
> Dr. M. Hank H. Stevens, Assistant Professor
> 338 Pearson Hall
> Botany Department
> Miami University
> Oxford, OH 45056
>
> Office: (513) 529-4206
> Lab: (513) 529-4262
> FAX: (513) 529-4243
> http://www.cas.muohio.edu/~stevenmh/
> http://www.muohio.edu/ecology/
> http://www.muohio.edu/botany/
> "E Pluribus Unum"
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm