[R-sig-ME] generalized linear mixed models: large differences when using glmmPQL or lmer with laplace approximation

Greg Snow Greg.Snow at imail.org
Tue Oct 7 20:31:20 CEST 2008

You make reference to my comment below, but I think you overstate my position a bit (the words in quotes are not a direct quote of what I said).

The original poster mentioned that 2 different methods gave 2 different models, one possibility is that one method gave a wrong model (biased in a non-good way), another possibility is that the predictor variables are correlated enough that there are multiple good models.  I merely pointed out that comparing the predicted values to the original values would be one way to possibly distinguish between the 2 cases.

Focusing too much on the predicted values can lead to overfitting, so we should not depend only on that.  P-values are useful in some cases, so I would not say "don't worry about the p-values" as a general statement.

The issue of editors wanting p-values even when they answer the wrong question is part of the result of statisticians doing to good a job of training other researchers.  Now it is our responsibility to continue to train them as to when to use certain tools.

Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org

> -----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 Ben Bolker
> Sent: Tuesday, October 07, 2008 11:44 AM
> To: Martijn Vandegehuchte; R Mixed Models
> Subject: Re: [R-sig-ME] generalized linear mixed models: large
> differences when using glmmPQL or lmer with laplace approximation
> Martijn Vandegehuchte wrote:
> > First of all, thanks a lot for the info.
> >
> > I know the differences seem small, but most ecological journals still
> > let their opinion about ecological relevance of predictors depend
> > completely on p-values... So I think I'll stick to lmer because of
> the
> > Laplace approximation.
>   Well, Laplace should be better anyway.  (If the difference were in
> the other direction -- non-significant with Laplace and significant
> with
> glmmPQL -- I would still tell you to use Laplace.)
>   To speak to Greg Snow's comment ("don't worry about p-values, just
> look at predictions") -- this is really tough.  I still don't know
> what to do about the compromise between how statistics should be done
> and how journal editors seem to insist it should be done ...
>   cheers
>    Ben
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

More information about the R-sig-mixed-models mailing list