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