[R] GLMM (lme4) vs. glmmPQL output
Douglas Bates
bates at stat.wisc.edu
Fri Jan 9 19:26:21 CET 2004
I believe the distinction is explained in the lme4 documentation but,
in any case, the standard errors and the approximate log-likelihood
for glmmPQL are from the lme model that is the last step in the
optimization. The corresponding quantities from GLMM are from another
approximation that should be more reliable.
"Dieter Menne" <dieter.menne at menne-biomed.de> writes:
> Dear List,
>
> As I understand, GLMM (in experimental lme4) and glmmPQL (MASS) do
> similar things using somewhat different methods. Trying both,
> I get the same coefficients, but markedly different std. errors and
> p-values.
> Any help in understanding the models tested by both procedures?
>
> Dieter Menne
>
>
> UseMASS<-T # must restart R after changing because of nlme/lme4 clash
> if (UseMASS){
> library(MASS)
> summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID,
> family = binomial, data = bacteria))
> } else
> {
> library(lme4)
> summary(GLMM(y ~ trt + I(week > 2), random = ~ 1 | ID,
> family = binomial, data = bacteria,method="PQL"))
> }
>
> (MASS output)
> Fixed effects: y ~ trt + I(week > 2)
> Value Std.Error DF t-value p-value
> (Intercept) 3.412012 0.5185028 169 6.580509 0.0000
> trtdrug -1.247355 0.6440627 47 -1.936698 0.0588
> trtdrug+ -0.754327 0.6453971 47 -1.168780 0.2484
> I(week > 2)TRUE -1.607256 0.3583378 169 -4.485310 0.0000
>
> (lme4 output)
> Fixed effects: y ~ trt + I(week > 2)
> Estimate Std. Error DF z value Pr(>|z|)
> (Intercept) 3.41202 3.93293 169 0.8676 0.3856
> trtdrug -1.24736 1.52156 47 -0.8198 0.4123
> trtdrug+ -0.75433 1.21963 47 -0.6185 0.5363
> I(week > 2)TRUE -1.60726 2.19660 169 -0.7317 0.4644
>
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--
Douglas Bates bates at stat.wisc.edu
Statistics Department 608/262-2598
University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/
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