[R-sig-ME] Logistisc regression (lmer) fitted by the Laplaceapproximation- references?
HDoran at air.org
Wed Jul 23 14:46:17 CEST 2008
Do you mean limitations of the laplace approximation or limits of a glmm
fit by lmer? If it is the former, one possible argument is that lmer
uses a second-order taylor series expansion. One might claim that going
out further in the taylor series is needed to get good approximations of
the integral. I, however, may not be one of those people.
I know for example that the HLM software package uses a 6 order taylor
series. Just last week, I had to replicate some work. I used lmer and
HLM to compare output. The R output and the HLM output matched exactly
to the 3th decimal place for the BLUPS and the fixed effects.
Even using lmer for IRT (rasch) work gives the same point esimtates for
the items (when they are treated as fixed effects) as I get in other IRT
software packages that use estimating algorithms other than laplace.
> -----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 R.S. Cotter
> Sent: Wednesday, July 23, 2008 6:10 AM
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Logistisc regression (lmer) fitted by the
> Laplaceapproximation- references?
> Dear all,
> I have sucessfully run Logistic regression by using
> generalized linear mixed-effects model (lmer) fitted by the
> Laplace approximation (lme4 package).
> Is there any limits that I should aware of by use of this
> model? I haven't found references for this model, could
> somone provide me with a reference from a article/book?
> My response is Yes or No and explanatory variables is
> categories (A,B,C and D), and random effect (ID, number of groups 7).
> Regards RS
> R-sig-mixed-models at r-project.org mailing list
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