pbkrtest (version 0.3-2)

PBmodcomp: Model comparison of mixed models using parametric bootstrap methods.

Description

Model comparison of mixed models using parametric bootstrap methods.

Usage

PBmodcomp(largeModel, smallModel, nsim = 200, ref = NULL, cl = NULL, details = 0)
## S3 method for class 'lm':
PBmodcomp(largeModel, smallModel, nsim = 200, ref = NULL, cl = NULL, details = 0)
## S3 method for class 'mer':
PBmodcomp(largeModel, smallModel, nsim = 200, ref = NULL, cl = NULL, details = 0)

Arguments

largeModel

A linear mixed effects model as fitted with the lmer() function in the lme4 package. This model muse be larger than smallModel (see below).

smallModel

A linear mixed effects model as fitted with the lmer() function in the lme4 package. This model muse be smaller than largeModel (see above).

nsim

The number of simulations to form the reference distribution.

ref

Vector containing samples from the reference distribution. If NULL, this vector will be generated using PBrefdist().

cl

A vector identifying a cluster; used for calculating the reference distribution using several cores. See examples below.

details

The amount of output produced. Mainly relevant for debugging purposes.

Details

Under the fitted hypothesis (i.e. under the fitted small model) nsim samples of the likelihood ratio test statistic (LRT) are generetated. Then p-values are calculated as follows: LRT: Assuming that LRT has a chi-square distribution. PBtest: The fraction of simulated LRT-values that are larger or equal to the observed LRT value. Bartlett: A Bartlett correction is of LRT is calculated from the mean of the simulated LRT-values Gamma: The reference distribution of LRT is assumed to be a gamma distribution with mean and variance determined as the sample mean and sample variance of the simulated LRT-values.

See Also

KRmodcomp PBrefdist

Examples

data(beets)
head(beets)
beet0<-lmer(sugpct~block+sow+harvest+(1|block:harvest), data=beets, REML=FALSE)
beet_no.harv <- update(beet0, .~.-harvest)
PBmodcomp(beet0, beet_no.harv, nsim=20)

## Vanilla
PBmodcomp(beet0, beet_no.harv, nsim=200)

## Simulate reference distribution separately:
refdist <- PBrefdist(beet0, beet_no.harv, nsim=200)
PBmodcomp(beet0, beet_no.harv, ref=refdist)

## Do computations with multiple processors:
## Number of cores:
(nc <- detectCores())
## Create clusters
cl <- makeCluster(rep("localhost", nc))

## Then do:
PBmodcomp(beet0, beet_no.harv, cl=cl)

## Or in two steps:
refdist <- PBrefdist(beet0, beet_no.harv, nsim=200, cl=cl)
PBmodcomp(beet0, beet_no.harv, ref=refdist)

## It is recommended to stop the clusters before quitting R:
stopCluster(cl)