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ERIC Number: EJ1111598
Record Type: Journal
Publication Date: 2007-May
Pages: 29
Abstractor: As Provided
ISSN: EISSN-2330-8516
Refinement of a Bias-Correction Procedure for the Weighted Likelihood Estimator of Ability. Research Report. ETS RR-07-23
Zhang, Jinming; Lu, Ting
ETS Research Report Series, May 2007
In practical applications of item response theory (IRT), item parameters are usually estimated first from a calibration sample. After treating these estimates as fixed and known, ability parameters are then estimated. However, the statistical inferences based on the estimated abilities can be misleading if the uncertainty of the item parameter estimates is ignored. Instead, estimated item parameters can be regarded as covariates measured with error. Along the line of this measurement-error-model approach, asymptotic expansions of the maximum likelihood estimator (MLE) and weighted likelihood estimator (WLE) of ability were derived by Zhang, Xie, Song, and Lu (2007). In this paper, we propose an estimator of an ability parameter based on the asymptotic formula of the WLE. A simulation study shows that the new estimator effectively reduces the bias of the MLE or WLE of ability caused by the uncertainty of the item parameter estimates not taken into account.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A