R help - Jun 2011 - Using MCMC sampling to estimate p values with a mixed model

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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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

	[[alternative HTML version deleted]]

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
>
>         [[alternative HTML version deleted]]
>
>______________________________________________
>R-help at r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
===============================================================Robert A.
LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral at lcfltd.com
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