[R] glmmPQL model selection

[stephenb]

Sorry for the late reply. 

Just use the first 90% of your data to fit and then predict the last 10% and
see which one is better.
If the random effects are not good it will become very obvious.

If the concern is with fixed effects then just use gls which puts the random
effects in the error and select model as usual.


Emmanuelle TASTARD wrote:
> 
> Hi,
> I’m sorry, I know that it is a recurrent question but I have not been
> able to find the response in the Rhelp archives.
> I think my data require the use of the glmmPQL function but I do not
> know how to make the model selection. Since the AIC and log-likelihood
> are apparently meaningless, how can we select the parameters for a model
> and compare the models to find which one fits best the data?  
> Thanks a lot
> Emmanuelle Tastard
>  
> Emmanuelle TASTARD
> UMR 5174 'Evolution et Diversité Biologique'  
> Université Paul Sabatier Bat 4R3
> 31062 TOULOUSE CEDEX 9 France
> tel : 05 61 55 67 59
>  
> 
> 	[[alternative HTML version deleted]]
> 
> 
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