[R] glmmPQL, log-likelihoods issue

[Andrew Perrin]

Sorry for my ignorance, but could you explain a little further?  I'm
guessing from your response that this makes the log-likelihood that is
quoted by glmmPQL a poor measure of model fit. Are there are statistics
that would be better for reporting model fit?

thanks.

----------------------------------------------------------------------
Andrew J Perrin - http://www.unc.edu/~aperrin
Assistant Professor of Sociology, U of North Carolina, Chapel Hill
clists at perrin.socsci.unc.edu * andrew_perrin (at) unc.edu


On Fri, 21 Nov 2003, Prof Brian Ripley wrote:

> glmmPQL does not fit by maximum likelihood, and what is being quoted is
> not a likelihood for the original problem.
>
> On Fri, 21 Nov 2003, Andrew Perrin wrote:
>
> > Greetings-
> >
> > a reviewer for a paper of mine noted an anomaly in some models I ran using
> > glmmPQL (from the MASS package).  Specifically, the models are three-level
> > hierarchical probit models estimated using PQL under R.  The anomaly is
> > that the log-likelihoods decrease (or, alternatively -2logLik increases)
> > as variables are added to the null model. This is unusual, and I'm trying
> > to figure out how to interpret it.  I've found some indication (e.g., at
> > http://www.ssicentral.com/hlm/hlm00150.htm) that PQL estimation doesn't
> > produce meaningful log-likelihoods, but I'm suspicious of that claim. Any
> > comments or advice would be helpful.
>
> --
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>
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