My understanding of lmer() & glmer() is that REML=TRUE only applies to
lmer() with family NULL.  With family specified in lmer there is an
implicit invocation of glmer(), which does not have REML as an option.   In
the example code, the explicit call to glmer() means that you don't have to
worry about REML for anova(m1,m2) LR tests of nested fixed effects models
in this case.  Diego's point is important for lmer() without family.




On Mon, Jan 7, 2013 at 12:49 PM, Steve Taylor <steve.taylor@aut.ac.nz>wrote:

> Obrigado, Diego.  Yes I have studied a little bit of information theory,
> tho my recollections are hazy.
>
> > you can not compare combinations of fixed effects of class "mer" with
> REML = TRUE.
> Curious then, that that's the default value, and that the default anova()
> does precisely that by comparing two models differing only in the fixed
> effects included.
>
> I'm aware of the objections, such as the danger of spurious relations.
>  But I cannot see why they prevent step(glmer()) when step(glm()) has been
> a standard feature in R for many years.  The real reason seems to be the
> fact that methods in package:stats don't work with S4 objects.
>
> With my sample size, I think the difference between AIC and AICc is
> negligible.
>
> cheers,
>     Steve
>
> -----Original Message-----
> From: r-sig-mixed-models-bounces@r-project.org [mailto:
> r-sig-mixed-models-bounces@r-project.org] On Behalf Of Diego Pujoni
> Sent: Tuesday, 8 January 2013 2:04a
> To: r-sig-mixed-models@r-project.org
> Subject: Re: [R-sig-ME] stepwise model selection (of fixed effects only)
> using AIC?
>
> Hi Steve, have you heard about Information-Theoretic Approach? It uses the
> value of AIC (or AICc) to choose the best hypothesis among many a priori
> hypothesis. In Anderson (2008) "Model Based Inference in the Life Sciences"
> we see recomendations against stepwise (or all possible models) because
> this can lead easily to spurious relations. The author recommend to create
> several a priori hypothesis (models), using knowledge about the system and
> then use the AICc to look for the best of them. Another thing that you have
> to pay attention is the fact that you can not compare combinations of fixed
> effects of class "mer" with REML = TRUE.
>
> A hug
>
> --
>                                                Diego PJ
>
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>
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-- 
-------------------------------------------
Tom Philippi
Quantitative Ecologist & Data Therapist

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