[R-sig-ME] lmer: LRT and mcmcpvalue for fixed effects

[Simon Blomberg]

On Tue, 2008-07-15 at 13:43 +0800, Julie Marsh wrote:

> 
> 
> Given that I am using 2 different tests for two different hypotheses I  
> still would have expected these p-values to be more similar. 

Well, as Pinheiro and Bates say in their book (worth reading!), the LRT
for mixed effects models is anti-conservative. So your LRT p-value is
almost certainly too small. The posterior p-value might be more
accurate, if you accept the usual caveats re: priors and convergence
etc. Also, when calculating p-values by hand using pchisq, you should
probably use pchisq(..., lower.tail=FALSE) instead of 1-pchisq(...),
which is inaccurate. The log.p option might also be useful if you really
need to compare small probabilities. And why were you using pchisq with
0 df (which always == 1)? I don't understand that at all.

> I am so  
> sorry that I can't post the data and the lmer output but I am bound by  
> confidentiality. <big sigh>  I understand completely if it is not  
> possible to provide any help given this lack of further information.
> 
> I have eagerly read and re-read the rwiki help page  .........
> 
> http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests
> 
> ....... but still am unable to explain why the results should be so  
> different. Much as I would love to argue against the reliance on  
> p-values I'm afraid I am a resigned pragmatist when it comes to trying  
> to get anything published.  <sorry!>  Needless to say I will swamp the  
> article with far more informative plots and CI's.
> 
> Any help would be very much appreciated.
> 
> kindest regards,  julie marsh.
> 
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-- 
Simon Blomberg, BSc (Hons), PhD, MAppStat. 
Lecturer and Consultant Statistician 
Faculty of Biological and Chemical Sciences 
The University of Queensland 
St. Lucia Queensland 4072 
Australia
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T: +61 7 3365 2506
http://www.uq.edu.au/~uqsblomb
email: S.Blomberg1_at_uq.edu.au

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