[R] lmer and method call
bates at stat.wisc.edu
Sat Dec 1 16:28:33 CET 2007
On Dec 1, 2007 9:26 AM, Douglas Bates <bates at stat.wisc.edu> wrote:
> On Nov 29, 2007 8:09 PM, M-J Milloy <mjmilloy at cfenet.ubc.ca> wrote:
> > Hello all,
> > I'm attempting to fit a generalized linear mixed-effects model using lmer
> > (R v 2.6.0, lmer 0.99875-9, Mac OS X 10.4.10) using the call:
> > vidusLMER1 <- lmer(jail ~ visit + gender + house + cokefreq + cracfreq +
> > herofreq + borcur + comc + (1 | code), data = vidusGD, family = binomial,
> > correlation = corCompSymm(form = 1 | ID), method = "ML")
> > Although the model fits, the summary indicates the model is a "Generalized
> > linear mixed model fit using Laplace". I've tried any number of
> > permutations; is only Laplace supported in lmer, despite the text of the
> > help file?
> The help file does say that for a generalized linear mixed model
> (GLMM), which is what family = binomial implies, the estimation
> criterion is always "ML" (maximum likelihood) as opposed to "REML"
> (restricted, or residual, maximum likelihood). So stating method =
> "ML" is redundant.
> For a GLMM, however, the log-likelihood cannot not be evaluated
> directly and must be approximated. Here the help file is misleading
> because it implies that there are three possible approximations, "PQL"
> (penalized quasi-likelihood), "Laplace" and "AGQ" (adaptive Gaussian
> quadrature). AGQ has not yet been implemented so the only effective
> choices are PQL and Laplace. The default is PQL, to refine the
> starting estimates, followed by optimization of the Laplace
> approximation. In some cases it is an advantage to suppress the PQL
> iterations which can be done with one of the settings for the control
I forgot to mention that the correlation argument has no effect in
this call. That argument is for the lme function in the nlme package.
In lmer it is ignored.
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