[R-sig-ME] false convergence glmer when quadratic terms are included

[Douglas Bates]

On Tue, May 19, 2009 at 5:32 AM, ONKELINX, Thierry
<Thierry.ONKELINX at inbo.be> wrote:
> Dear Stijn,

> Why don't you use poly(x, 2) instead? Adding x^2 with large or small
> values will lead to even larger or smaller values. That may cause the
> model to become unstable. Poly(x, 2) will avoid that by rescaling.

> glmer(y~(1|level2id)+poly(x,2),family=binomial,data=data)

Exactly.

The general advice in a case like this is to add the optional argument

verbose = TRUE

in the call to glmer so that you get a display of the progress of the
iterations.   Take a look at

example(cbpp)

You will see that a line in the trace output is of the form

 16:     100.09586: 0.642264 -1.39853 -0.992327 -1.12866 -1.58032

where the first number is the iteration number, the second is the
current value of the deviance, the third is the standard deviation of
the random effects and the fourth and subsequent numbers are the
values of the fixed-effects parameters.  It is likely that one of the
fixed-effects parameters is very large or very small in your original
form of the model.


>
> HTH,
>
> Thierry
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
> tel. + 32 54/436 185
> Thierry.Onkelinx at inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to
> say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of
> data.
> ~ John Tukey
>
> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces at r-project.org
> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Stijn Ruiter
> Verzonden: dinsdag 19 mei 2009 12:18
> Aan: r-sig-mixed-models at r-project.org
> Onderwerp: [R-sig-ME] false convergence glmer when quadratic terms are
> included
>
> Dear all,
> Somehow I always get false convergence warnings when including a
> quadratic term in a glmer equation. With lmer I have no such problems.
> So, my guess is that this has to do with the different algorithm used
> for glmer models.
> The following example model (which can easily be estimated in
> alternative mixed effects programs such as MLwiN or HLM) result in
> problems:
>
> glmer(y~(1|level2id)+x+I(x^2),family=binomial,data=data)
>
> It leads to:
> Warning message:
> In mer_finalize(ans) : false convergence (8)
>
> What is the problem here? Why these convergence issues?
>
> Stijn
>
> --
> Best regards,
>
> Stijn Ruiter
> Department of Sociology / ICS
> Radboud University Nijmegen
> P.O. Box 9104
> 6500 HE Nijmegen
> Netherlands
>
> Phone: + 31 24 361 2272
> Fax:   + 31 24 361 2399
>
> Visiting address:
> Thomas van Aquinostraat 4.01.71
> Nijmegen
>
> website: http://oase.uci.ru.nl/~sruiter
>
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