[R] AIC in lmer when using PQL
Dimitris Rizopoulos
dimitris.rizopoulos at med.kuleuven.be
Thu Nov 24 10:33:40 CET 2005
note that although PQL is the default method in lmer() for GLMMs, the
recent version of the function allow also for Laplace or adaptive
Gauss-Hermite approximations. In these cases it might be reasonable to
compute AIC values depending on how good the approximation to the
likelihood is; however, the use of AIC in mixed models can be tricky
depending on the focus of your analysis, check e.g.,
Vaida, F. and Blanchard, S. (2005). Conditional Akaike information for
mixed-effects models, Biometrika, 92, 351-370.
Regarding inference, I'd rely mainly on LRTs instead of Wald type
p-values.
I hope it helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://www.med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Elizabeth Boakes" <Elizabeth.Boakes at ioz.ac.uk>
To: <r-help-request at stat.math.ethz.ch>; <r-help at stat.math.ethz.ch>
Sent: Thursday, November 24, 2005 9:53 AM
Subject: [R] AIC in lmer when using PQL
>I am analysing binomial data using a generalised mixed effects model.
>I
> understand that if I use glmmPQL it is not appropriate to compare
> AIC
> values to obtain a minimum adequate model.
>
>
>
> I am assuming that this means it is also inappropriate to use AIC
> values
> from lmer since, when analysing binomial data, lmer also uses PQL
> methods. However, I wasn't sure so please could somebody clarify
> this
> for me.
>
>
>
> I was also wondering how best to assess your minimum adequate model
> without AIC values? Do you simply have to rely on the p values
> associated with the t-values/z-values?
>
>
>
> Thanks very much.
>
> Elizabeth Boakes
>
>
>
> Elizabeth Boakes
> PhD Student
> Institute of Zoology
> Regent's Park
> London NW1 4RY
> tel: 020 7449 6621
>
>
>
>
>
> _________________________________________________________________________
> This e-mail has been sent in confidence to the named\ > ad...{{dropped}}
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