boot.LR: Parametric bootstrap likleihood-ratio test

In xzhaopsy/MIRT: Multidimensional Item Response Theory

Description

Given two fitted models, compute a parametric bootstrap test to determine whether the less restrictive models fits significantly better than the more restricted model. Note that this hypothesis test also works when prior parameter distributions are included for either model. Function can be run in parallel after using a stuitable mirtCluster definition.

Usage

boot.LR(mod, mod2, R = 1000)

Arguments

mod	an estimated model object
mod2	an estimated model object
R	number of parametric bootstraps to use.

Value

a p-value evaluating whether the more restrictive model fits significantly worse than the less restrictive model

Author(s)

Phil Chalmers [e-mail]

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06

Examples

## Not run: 

#standard
dat <- expand.table(LSAT7)
mod1 <- mirt(dat, 1)
mod2 <- mirt(dat, 1, '3PL')

# standard LR test
anova(mod1, mod2)

# bootstrap LR test (run in parallel to save time)
mirtCluster()
boot.LR(mod1, mod2, R=200)


## End(Not run)

xzhaopsy/MIRT documentation built on May 29, 2019, 12:42 p.m.