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

In irtoys: A Collection of Functions Related to Item Response Theory (IRT)

Bias-corrected (Warm's) estimates of ability

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: the object returned by est.

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)

irtoys documentation built on May 12, 2022, 5:06 p.m.