[R-sig-ME] lmer: LRT and mcmcpvalue for fixed effects
s.blomberg1 at uq.edu.au
Tue Jul 15 09:00:22 CEST 2008
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 .........
> ....... 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.
> R-sig-mixed-models at r-project.org mailing list
Simon Blomberg, BSc (Hons), PhD, MAppStat.
Lecturer and Consultant Statistician
Faculty of Biological and Chemical Sciences
The University of Queensland
St. Lucia Queensland 4072
Room 320 Goddard Building (8)
T: +61 7 3365 2506
1. I will NOT analyse your data for you.
2. Your deadline is your problem.
The combination of some data and an aching desire for
an answer does not ensure that a reasonable answer can
be extracted from a given body of data. - John Tukey.
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