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.