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 <[EMAIL PROTECTED]> 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. > > > > Jérôme Lemaître > > > Ph.D. student > Silviculture-wildlife research chair in irregular boreal forests > & Départment 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: [EMAIL PROTECTED] > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
