mirt (version 1.9)

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. Object returns the confidence intervals and whether the respective interval could be found.

Usage

PLCI.mirt(mod, alpha = 0.05, parnum = NULL, plot = FALSE, npts = 24,
  ...)

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

plot

logical; plot the parameter relationship in the likelihood space for two parameters?

npts

number of points to evaluate and plot if plot = TRUE

...

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

# plot the confidence envelope for parameters 1 and 2
PLCI.mirt(mod2, parnum=c(1,2), plot=TRUE)