wle: Bias-corrected (Warm's) estimates of ability

In lebebr01/irtoys-2: Simple interface to the estimation and plotting of IRT models

Description

Weighted likelihood estimates (WLE) of ability, designed to remove the first order bias term from the ML estimates. WLE are finite for response patterns consisting of either uniformly wrong or uniformly correct responses.

Usage

  wle(resp, ip)

Arguments

resp	A matrix of responses: persons as rows, items as columns, entries are either 0 or 1, no missing data
ip	Item parameters: a matrix with one row per item, and three columns: [,1] item discrimination a, [,2] item difficulty b, and [,3] asymptote c.

Value

A matrix with the ability estimates in column 1, and their standard errors of measurement (SEM) in column 2, and the number of non-missing reponses in column 3

Author(s)

Ivailo Partchev

References

Warm T.A. (1989) Weighted Likelihood Estimation of Ability in Item Response Theory. Psychometrika, 54, 427-450.

See Also

mlebme, eap

Examples

th.bce <- wle(resp=Scored, ip=Scored2pl$est)

lebebr01/irtoys-2 documentation built on May 20, 2019, 11:29 p.m.