Re: [R] zero random effect sizes with binomial lmer

From: Andrew Robinson <A.Robinson_at_ms.unimelb.edu.au>
Date: Mon 01 Jan 2007 - 19:19:29 GMT

According to pp 197-198 of MASS 4, the Hauck-Donner phenomenon refers to cases when the Wald approximations and the likelihood ratio tests have different p values because of the former underestimating the the change in log-likelihood on setting \beta_i = 0.

This seems quite different to me than the phenomenon that Daniel is reporting, and that I believe I saw previously (post: http://tolstoy.newcastle.edu.au/R/e2/help/06/12/6903.html )

I tried an earlier version of R, on a different platform, and got quite different results. Sadly, the *earlier* results are the ones that make sense.

eg:

> sessionInfo()

R version 2.4.1 Patched (2006-12-30 r40330) i386-unknown-freebsd6.1

locale:
C

attached base packages:

[1] "stats"     "graphics"  "grDevices" "utils"   "datasets"  "methods"  
[7] "base"     

other attached packages:
       lme4      Matrix     lattice 

"0.9975-10" "0.9975-6" "0.14-16"
> ranef(lmer(Reaction ~ Days + (1|Subject), sleepstudy,

       family=Gamma(link="log")))
An object of class "ranef.lmer"
[[1]]

      (Intercept)

308  6.817268e-10
309 -1.369242e-09
310 -1.122033e-09
330  1.164825e-10
331  2.096848e-10
332  1.494418e-10
333  3.042078e-10
334 -6.276876e-11
335 -7.556428e-10
337  1.263863e-09
349 -3.984973e-10
350  2.107439e-10
351 -1.230185e-10
352  6.409427e-10
369  1.224258e-10
370 -1.528146e-10
371 -5.310404e-11
372  3.228682e-10



> sessionInfo()

Version 2.3.1 (2006-06-01)
i386-pc-mingw32

attached base packages:
[1] "methods" "stats" "graphics" "grDevices" "utils" "datasets" [7] "base"

other attached packages:

      lme4 Matrix lattice
 "0.995-2" "0.995-20" "0.13-8"
> ranef(lmer(Reaction ~ Days + (1|Subject), sleepstudy,
+ family=Gamma(link="log")))
An object of class "ranef.lmer"
[[1]]

     (Intercept)

308  0.128473227
309 -0.294234827
310 -0.232009186
330  0.029091372
331  0.046196655
332  0.035400265
333  0.063273674
334 -0.004238362
335 -0.147285458
337  0.220381662
349 -0.070565390
350  0.046822487
351 -0.015994000
352  0.121461879
369  0.030457370
370 -0.021387277
371 -0.002494534
372  0.066650443

>

Cheers,

Andrew

On Mon, Jan 01, 2007 at 06:09:12PM +0000, Dieter Menne wrote:
> Daniel Ezra Johnson <johnson4 <at> babel.ling.upenn.edu> writes:
>
> >
> > I am fitting models to the responses to a questionnaire that has
> > seven yes/no questions (Item). For each combination of Subject and
> > Item, the variable Response is coded as 0 or 1.
> >
> > I want to include random effects for both Subject and Item. While I
> > understand that the datasets are fairly small, and there are a lot of
> > invariant subjects, I do not understand something that is happening
> > here, and in comparing other subsets of the data.
> >
> > In the data below, which has been adjusted to show this phenomenon
> > clearly, the Subject random effect variance is comparable for A
> > (1.63) and B (1.712), but the Item random effect variance comes out
> > as 0.109 for B and essentially zero for A (5.00e-10).
> ...
>
> Check the list archives for quite a few postings of Professor Brian Ripley on
> the subject of Hauk-Donner.
>
>
> Dieter
>
> ______________________________________________
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-- 
Andrew Robinson  
Department of Mathematics and Statistics            Tel: +61-3-8344-9763
University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599
http://www.ms.unimelb.edu.au/~andrewpr
http://blogs.mbs.edu/fishing-in-the-bay/

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Received on Tue Jan 02 06:34:42 2007

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