aovlmer.fnc {languageR} | R Documentation |
This function computes p-values for factors in a mixed-effects model. A p-value is returned based on an MCMC sample, as well as the anova table output by lmer extended with the p-values based on denominator degrees of freedom equal to the number of observations minus the number of fixed-effects coefficients. For small datasets, this p-value is anticonservative.
aovlmer.fnc(object, mcmc, which, noMCMC, ...)
object |
An lmer or glmer model for a response variable
fitted with lmer . |
mcmc |
A Markov chain Monte Carlo sample obtained with
pvals.fnc(..., withMCMC=TRUE)$mcmc for the lmer model. |
which |
A vector of integers or strings denoting the rows in the table of coefficients that specify the coefficients for the factor. |
noMCMC |
A logical indicating whether MCMC sampling should be skipped, in which case a data frame with a traditional ANOVA table is returned. |
... |
Other optional arguments. |
When noMCMC == FALSE
, a list with components
MCMC |
A list with the empirical p-value for the hypothesis
that the columns of an MCMC sample specified by which have
mean zero versus a general multivariate distribution with elliptical
contours, and the rownames specified by which .
|
Ftests |
An anova table listing the (anticonservative) p-value based on the F-test. This table is also returned when noMCMC is set to TRUE. |
R. H. Baayen, D. Bates
See also lmer, mcmcsamp.
## Not run: library(lme4, keep.source=FALSE) library(coda) data(latinsquare) l.lmer = lmer(RT~SOA+(1|Word)+(1|Subject), data=latinsquare) mcmc = pvals.fnc(l.lmer, nsim=10000, withMCMC=TRUE) aovlmer.fnc(l.lmer, mcmc$mcmc, c("SOAmedium", "SOAshort")) ## End(Not run)