[R-sig-ME] warnings ranef and design of a binomial model
Robert.Espesser at lpl-aix.fr
Wed Sep 10 19:18:47 CEST 2008
> From: Douglas Bates <bates at stat.wisc.edu>
> Sent: Wed Sep 10 15:43:38 CEST 2008
> To: Robert ESPESSER <Robert.Espesser at lpl-aix.fr>
> Subject: Re: [R-sig-ME] warnings ranef and design of a binomial model
>I think we would need at least the output from traceback() to see
>where the error is occurring. Better yet would be to have access to
>the data so we could try out the model fits. Sometimes these errors
>show up deep inside another computation. Does
>produce a result? I'm trying to decide if the problem is in the
>postVar part or in the ranef part.
The warning messages are output by dotplot(ranef() ).
ranef(xxx ,postVar=T) by itself does not output any warning messages.
modG.glmer <- glmer( vd ~ dlms*expe +(dlms|subject) ,family=binomial, ....)
modI.glmer <- glmer( vd ~ dlms*expe +(1|subject) ,family=binomial, ....)
modS.glmer <- glmer( vd ~ dlms*expe +(0+dlms|subject) ,family=binomial, ....)
have their dotplot(ranef()) OK.
The problem is only with the model:
modIS.glmer <- glmer( vd ~ dlms*expe +(1|subject) +(0+dlms|subject) ,family=binomial, ....)
> dotplot( rr.glmer)
1: In min(x) : aucun argument trouvé pour min ; Inf est renvoyé
2: In max(x) : aucun argument pour max ; -Inf est renvoyé
traceback() returns nothing :
(because I have tested it with the example in ?traceback)
In addition, how can I extract the postVar component in a ranef object ?
Dr Bates, in case you need the data , do I have attach them in a private mail to you ?
here is the complete sessionInfo():
R version 2.7.2 (2008-08-25)
attached base packages:
 stats graphics grDevices datasets utils methods base
other attached packages:
 lme4_0.999375-26 Matrix_0.999375-13 lattice_0.17-13
loaded via a namespace (and not attached):
 grid_2.7.2 nlme_3.1-89
> On Wed, Sep 10, 2008 at 5:29 AM, Robert ESPESSER
> <Robert.Espesser at lpl-aix.fr> wrote:
> > Dear R users,
> > I have a question about model design.
> > One group of 20 subjects run the A experiment, with 17 binary responses by subject.
> > An other group of 20 subjects run the 2 experiments B and C, with 20 binary responses by subject,
> > for both of the 2 experiment.
> > I want to study the effect of the factor "expe"
> > I tried this covariance model:
> > mod.glmer <- glmer( vd ~ dlms*expe +(1|subject) +(0+dlms|subject) ,
> > family=binomial, ....)
> > where:
> > dlms is a numeric factor (-2,-1,0, 1,2)
> > expe is a 3 levels factor , coding the experiment (A or B or C)
> > vd is the success/fail matrix.
> > The model with a random slope is clearly better than an intercept-only model.
> > the results look plausible, ranef(mod.glmer, postVar=T) was OK for the
> > Intercept, but failed
> > to compute the postvar of the random slope , with these warnings:
> > 1: In min(x): no argument found for min; Inf is returned
> > It's the same for max.
> > I'm suspecting that my model is perhaps badly designed , concerning the
> > unbalanced repartition of the subjects across the experiments. Is it correct ?
> > Thanks for any comments or suggestions.
> > ####
> > sessionInfo() is:
> > R version 2.7.2
> > lme4_0.999375-26
> > Matrix_0.999375-13
> > Robert Espesser
> > Laboratoire Parole et Langage UMR 6057, CNRS
> > 29 Av. Robert Schuman 13621 AIX (FRANCE)
> > Tel: +33 (0)4 42 95 36 26 Fax: +33 (0)4 42 95 37 88
> > http://www.lpl-aix.fr
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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