posteriorKL: Expected Kullback-Leibler Information, Weighted by the Prior

In erossiter/catSurv: Computerized Adaptive Testing for Survey Research

Expected Kullback-Leibler Information, Weighted by the Prior

Description

Calculates the expected Kullback-Leibler information, weighted by likelihood and prior beliefs, for a specified item.

Usage

posteriorKL(catObj, item)

Arguments

catObj	An object of class Cat
item	An integer indicating the index of the question item

Details

The function posteriorKL calculates the expected Kullback-Leibler information for question item, where the proposed values of the true ability parameter are weighted by the prior.

This function involves integration. See Note for more information.

Value

The function posteriorKL returns a numeric indicating the expected Kullback-Leibler information weighted by the likelihood for the specified item, given the current answer profile and ability parameter estimate.

Note

This function is to allow users to access the internal functions of the package. During item selection, all calculations are done in compiled C++ code.

This function uses adaptive quadrature methods from the GNU Scientific Library (GSL) to approximate single-dimensional integrals with high accuracy. The bounds of integration are determined by the lowerBound and upperBound slots of the Cat object.

Author(s)

Haley Acevedo, Ryden Butler, Josh W. Cutler, Matt Malis, Jacob M. Montgomery, Tom Wilkinson, Erin Rossiter, Min Hee Seo, Alex Weil

See Also

expectedKL, likelihoodKL, selectItem

Examples

## Loading ltm Cat object
data(ltm_cat)

## Store example answers
setAnswers(ltm_cat) <- c(1,0,1,0,1, rep(NA, 35))

## Estimate EPV for different unasked items
posteriorKL(ltm_cat, item = 10)
posteriorKL(ltm_cat, item = 20)
posteriorKL(ltm_cat, item = 30)

erossiter/catSurv documentation built on Dec. 11, 2022, 6:36 p.m.