mirt (version 1.42)

testinfo: Function to calculate test information

Description

Given an estimated model compute the test information.

Usage

testinfo(
  x,
  Theta,
  degrees = NULL,
  group = NULL,
  individual = FALSE,
  which.items = 1:extract.mirt(x, "nitems")
)

Arguments

x

an object of class 'SingleGroupClass', or an object of class 'MultipleGroupClass' if a suitable group input were supplied

Theta

a matrix of latent trait values

degrees

a vector of angles in degrees that are between 0 and 90. Only applicable when the input object is multidimensional

group

group argument to pass to extract.group function. Required when the input object is a multiple-group model

individual

logical; return a data.frame of information traceline for each item?

which.items

an integer vector indicating which items to include in the expected information function. Default uses all possible items

Author

Phil Chalmers

References

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

Examples

dat <- expand.table(deAyala)
(mirt(dat, 1, '2PL', pars = 'values'))
mod <- mirt(dat, 1, '2PL', constrain = list(c(1,5,9,13,17)))

Theta <- matrix(seq(-4,4,.01))
tinfo <- testinfo(mod, Theta)
plot(Theta, tinfo, type = 'l')

if (FALSE) {

# compare information loss between two tests
tinfo_smaller <- testinfo(mod, Theta, which.items = 3:5)

# removed item informations
plot(Theta, iteminfo(extract.item(mod, 1), Theta), type = 'l')
plot(Theta, iteminfo(extract.item(mod, 2), Theta), type = 'l')

# most loss of info around -1 when removing items 1 and 2; expected given item info functions
plot(Theta, tinfo_smaller - tinfo, type = 'l')


}