false convergence glmer when quadratic terms are included
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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