[R-lang] p-values from pvals.fnc

[Jakke Tamminen]

Dear R-users,

I have been wondering about something with the pvals.fnc function. As we
know, the pvals function gives two p-values, one based on the posterior
distribution (pMCMC) and one based on the t-distribution. In my experience
most of the time the two values are very similar. However, I have recently
come across situations where they are wildly different. I have been
particularly surprised to see t-values above 2 that have associated pMCMC
values that are not even close to significance, while at the same time the
t-distribution based p-value is significant. For example, a recent model I
worked with looked something like this:

model1 = lmer(RT~x*y+(1+x|Subject)+(1|Item)

and gave me a t-value of 2.07 for the interaction, with a pMCMC p-value of
0.4756 and a t-distribution p-value of 0.0381. Obviously I like one of these
better than the other! I know that the latter p-value is anticonservative,
but the magnitude of the discrepancy is nonetheless surprising to me, given
the t-value. I'd be very grateful for any advice on how to proceed in cases
like this. I'm using lme4 version 0.99875-6.

Many thanks,

Jakke
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