[R] lmer4 and variable selection

Prof Brian Ripley ripley at stats.ox.ac.uk
Mon Aug 25 20:29:36 CEST 2008


On Mon, 25 Aug 2008, jebyrnes wrote:

>
> Have you thought about using AIC weights?  As long as you are not considering
> models where you drop your random effects, calculating AIC values (or AICc
> values) and doing multimodel inference is one way to approach your problem.
>
> If you are fitting models with and without random effects, it gets trickier
> - see Vaida and Blanchard 2005 Biometrika.

Also if you are setting variances to zero ....

>
> -Jarrett
> -- 
> View this message in context: http://www.nabble.com/lmer4-and-variable-selection-tp19146850p19147125.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

-- 
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



More information about the R-help mailing list