Could you try this model fit again adding control = list(usePQL FALSE,
msVerbose=TRUE) to the argument list of the call to lmer? By
default PQL iterations are used at the beginning of a generalized
linear mixed model fit followed by optimization of the Laplace
approximation to the log-likelihood when method = "Laplace".
Sometimes the PQL iterations do more harm than good and you do better
going straight to the optimization of the Laplace approximation.
On 9/6/06, jerome lemaitre <jerome.lemaitre.1 at ulaval.ca>
wrote:> Dear all,
>
> I get an error message when I run my model and I am not sure what to do
> about it.
>
> I try to determine what factors influence the survival of voles. I use a
> mixed-model because I have several voles per site (varying from 2 to 19
> voles).
>
> Here is the model:
> ###
> fm5 <-lmer(data=cdrgsaou2,
>
alive~factor(pacut)+factor(agecamp)+factor(sex)+ResCondCorp+(1|factor(cdrgsa
> ou2$ids)),
> family=binomial,
> method="Laplace",
> )
> ###
> Description of variables
> Alive: 0 or 1; dead or alive
> pacut: 0 or 1; presence of parasites
> agecamp: a or j; adult or juvenile
> sex: m or f; male or female
> ResCondCorp: body condition, continuous;
> cdrgsaou2$ids: name of the site.
>
>
> Here is the output:
>
> ###
> Generalized linear mixed model fit using Laplace
> Formula: alive ~ factor(pacut) + factor(agecamp) + factor(sex) +
ResCondCorp
> + (1 | factor(cdrgsaou2$ids))
> Data: cdrgsaou2
> Family: binomial(logit link)
> AIC BIC logLik deviance
> 305.7418 328.7331 -146.8709 293.7418
> Random effects:
> Groups Name Variance Std.Dev.
> factor(cdrgsaou2$ids) (Intercept) 0.034382 0.18542
> number of obs: 341, groups: factor(cdrgsaou2$ids), 36
>
> Estimated scale (compare to 1) 2.174681
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 0.971458 0.250951 3.8711 0.0001083 ***
> factor(pacut)1 -0.831888 0.358583 -2.3199 0.0203447 *
> factor(agecamp)j -1.294236 0.330638 -3.9144 9.065e-05 ***
> factor(sex)m 0.581713 0.296229 1.9637 0.0495616 *
> ResCondCorp -0.176251 0.020263 -8.6982 < 2.2e-16 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
>
> Correlation of Fixed Effects:
> (Intr) fct()1 fctr(g) fctr(s)
> factr(pct)1 -0.334
> fctr(gcmp)j -0.417 0.066
> factor(sx)m -0.505 -0.002 -0.173
> ResCondCorp -0.309 -0.010 0.302 -0.032
> ###
>
> Here is the error message:
>
> ###
> Warning message:
> Estimated variance for factor 'factor(cdrgsaou2$ids)' is
effectively zero
> in: LMEopt(x = mer, value = cv)
> ###
>
> Thank you very much by advance for any help.
>
>
>
> J?r?me Lema?tre
>
>
> Ph.D. student
> Silviculture-wildlife research chair in irregular boreal forests
> & D?partment of biology,
> Faculty of Sciences and Engineering
> Alexandre-Vachon building
> University Laval
> Quebec, QC G1K 7P4
> Phone : (418) 656-2131 poste 2917
> Office : VCH-2044
> Email: jerome.lemaitre.1 at ulaval.ca
>
> ______________________________________________
> 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
> and provide commented, minimal, self-contained, reproducible code.
>