Dear Francisco, as Roger said, too strong correlations between the variances of the random effects can lead to a singularity in the estimation of the variance-covariance matrix for the random effects. This can also happen, if any of the variances are indistinguishable from zero. Like Roger, I do not have a clear understanding of the underlying fitting procedure, but too the best of my knowledge the singularity is due to one of the underlying parameters determining the random effects whose value is being optimized is too close to zero.
I suggest the following: look at the a couple of different models. I would start by comparing a model with only a random intercept vs. a model with only the random slopes (the "type | spk" part). If a model with only the random slopes does not converge, the singularity due to some of the levels of "type" being indistinguishable with regard to their random effects and you should do what Roger suggested. If the model with only random slopes DOES converge, you can compare it against a model with only the random intercept. Too a first approximation, you may use the model fit measures, e.g. AIC to compare the two models. When you compare these models, keep in mind that the slopes have more DFs than just the intercept. If a model with only the random intercept has basically the same model fit quality as a model with only the random slopes, than it seems that (given the fixed effects that you are considering) the random slopes do not seem to do much ( i.e. the different types do not seem to affect your dependent variable, at least not under the assumption that their effect is normally distributed). Have a look at Baayen, Davidson, & Bates, 07 for more detail on how to compare different models based on their random effects. Florian On 6/23/07, Francisco Torreira <[EMAIL PROTECTED]> wrote: > > Hello, > > I am fitting a mixed model that prompts the following warning messages: > > Warning messages: > 1: Estimated variance-covariance for factor 'spk' is singular > in: `LMEoptimize<-`(`*tmp*`, value = list(maxIter = 200L, tolerance = > 1.49011611938477e-08, > 2: nlminb returned message function evaluation limit reached without > convergence (9) > in: `LMEoptimize<-`(`*tmp*`, value = list(maxIter = 200L, tolerance = > 1.49011611938477e-08, > > Although the model is fitted, R does not let me run simulations on it > with mcmcamp(). This is the error message I get: > > > mcmcsamp(full, n=10000) > Error: inconsistent degrees of freedom and dimension > Error in t(.Call(mer_MCMCsamp, object, saveb, n, trans, verbose, > deviance)) : > error in evaluating the argument 'x' in selecting a method for > function 't > > The model was: > full <- lmer(an ~ type + (1 + type | spk) - 1) > > My design included 5 speakers (spk) and 5 utterance types (type). For > each combination of speaker and utterance type there were > approximately 20 repetitions. If I fit a more reduced model with no > random effect for type within speakers, as in lmer(an~type+(1|spk)), > no warning appears. Here is the summary of my full model: > > Linear mixed-effects model fit by REML > Formula: an ~ 1 + type + (1 + type | spk) - 1 > AIC BIC logLik MLdeviance REMLdeviance > 4663 4747 -2311 4653 4623 > Random effects: > Groups Name Variance Std.Dev. Corr > spk (Intercept) 1568.3 39.601 > typee 1037.3 32.208 -0.745 > typeg 1303.7 36.107 -0.659 0.946 > typei 1780.9 42.200 -0.778 0.976 0.864 > typel 757.4 27.521 -0.725 0.839 0.826 0.865 > Residual 598.8 24.470 > number of obs: 498, groups: spk, 5 > > Fixed effects: > Estimate Std. Error t value > typea 78.87 17.88 4.410 > typee 18.49 12.13 1.524 > typeg 50.86 14.26 3.566 > typei 11.42 12.48 0.915 > typel 14.94 12.46 1.199 > > Correlation of Fixed Effects: > typea typee typeg typei > typee 0.570 > typeg 0.491 0.898 > typei 0.240 0.851 0.722 > typel 0.699 0.758 0.739 0.622 > > I wonder if the high correlations correlations between several > utterance types and the intercept in the random part of the model > aren't causing all this trouble. I would appreciate any comment on the > warnings. > > Thanks in advance, > Francisco Torreira > > -- > Francisco Torreira > PhD Candidate in Hispanic Linguistics > University of Illinois at Urbana-Champaign > > https://netfiles.uiuc.edu/ftorrei2/www/index.html > tel: (+1) 217 - 778 8510 > _______________________________________________ > R-lang mailing list > [email protected] > https://ling.ucsd.edu/mailman/listinfo.cgi/r-lang >
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