Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-
> models-bounces at r-project.org] On Behalf Of jos matejus
> Sent: Monday, July 27, 2009 8:19 AM
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] modelling saturated random effects with glmm
>
> Dear all,
>
> I was wondering whether anyone could enlighten me on the following.
>
> Why is it I can fit a generalized linear mixed model (family = poisson
> for example) with lmer where I have as many levels of my random effect
> as data points whereas with a linear mixed effects model (gaussian
> distributed errors) I get an error message. I understand that the
> random effect variance is completely confounded with the residual
> variance in the case of a linear mixed model, but why is this not so
> with a generalized linear mixed model?
>
> for example
>
> data(ergoStool, package="nlme") # load data
> ergoStool$rantest <- 1:36 #create a pseudo random effect to illustrate
>
> library(lme4)
>
> stool.lmm <- lmer(effort~Type+(1|rantest), data=ergoStool)
> #Error: length(levels(dm$flist[[1]])) < length(Y) is not TRUE
>
> stool.glmm <- lmer(effort~Type+(1|rantest) , family=poisson,
> data=ergoStool)
>
> summary(stool.glmm)
>
> Generalized linear mixed model fit by the Laplace approximation
> #Formula: effort ~ Type + (1 | rantest)
> Data: ergoStool
> AIC BIC logLik deviance
> 19.47 27.39 -4.737 9.474
> Random effects:
> Groups Name Variance Std.Dev.
> rantest (Intercept) 0 0
> Number of obs: 36, groups: rantest, 36
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 2.14658 0.11396 18.836 <2e-16 ***
> TypeT2 0.37469 0.14804 2.531 0.0114 *
> TypeT3 0.23091 0.15263 1.513 0.1303
> TypeT4 0.07503 0.15823 0.474 0.6354
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Correlation of Fixed Effects:
> (Intr) TypeT2 TypeT3
> TypeT2 -0.770
> TypeT3 -0.747 0.575
> TypeT4 -0.720 0.554 0.538
>
> Many thanks in advance
> Jos
>
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