Using MCMC sampling to estimate p values with a mixed model
If your alternative hypothesis is unequal variances (2-sided), both F < 1 and F > 1 are of interest, and rejection of the equal variance null can occur on either side. The usual ANOVA F test is 1-sided, with an alternative the numerator variance exceeds the denominator one, so this is perhaps why you are confused.
At 02:40 PM 6/18/2011, Woodcock, Helena wrote:
Hi everyone,
Apologies if this is a silly question but I am a student and this is
my first time using R so I am still trying to educate myself on
commands, models e.t.c
I have a mixed model with four dichotomous fixed factors and subject
as a random factor (as each person completed four vignettes, with
factors crossed across vignettes).
I have run an lmer model and used the Monte Carlo method to see if
there are any significant main effects or interactions. However,
when I looked at the p values some are showing as significant
although the F value is less than 1. Is it possible to have a
significant effect with an F value below 1?.
I have a sample size of 150 and have read that the pMCMC values can
be anti-conservative so wonder if it is because my sample size may
be too small?.
Thank you for any help
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