mirt (version 1.6.1)

PLCI.mirt: Compute profiled-likelihood confidence intervals

Description

Computes profiled-likelihood based confidence intervals. Supports the inclusion of prior parameter distributions as well as equality constraints.

Usage

PLCI.mirt(mod, alpha = 0.05, parnum = NULL, ...)

Arguments

mod

a converged mirt model

alpha

two-tailed alpha critical level

parnum

a numeric vector indicating which parameters to estimate. Use mod2values to determine parameter numbers. If NULL, all possible parameters are used

...

additional arguments to pass to the estimation functions

See Also

boot.mirt

Examples

mirtCluster() #use all available cores to estimate CI's in parallel
dat <- expand.table(LSAT7)
mod <- mirt(dat, 1)

result <- PLCI.mirt(mod)
result

mod2 <- mirt(Science, 1)
result2 <- PLCI.mirt(mod2)
result2

#only estimate CI's slopes
sv <- mod2values(mod2)
parnum <- sv$parnum[sv$name == 'a1']
result3 <- PLCI.mirt(mod2, parnum=parnum)
result3