Bias-corrected (Warm's) estimates of ability
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.
wle(resp, ip)
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. |
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
Ivailo Partchev
Warm T.A. (1989) Weighted Likelihood Estimation of Ability in Item Response Theory. Psychometrika, 54, 427-450.
th.bce <- wle(resp=Scored, ip=Scored2pl)
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