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On the Relationships between Jeffreys Modal and Weighted Likelihood Estimation of Ability under Logistic IRT Models

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Bibliographic Details
Title: On the Relationships between Jeffreys Modal and Weighted Likelihood Estimation of Ability under Logistic IRT Models
Language: English
Authors: Magis, David, Raiche, Gilles
Source: Psychometrika. Jan 2012 77(1):163-169.
Availability: Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Peer Reviewed: Y
Page Count: 7
Publication Date: 2012
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Item Response Theory, Computation, Bayesian Statistics, Models, Ability
DOI: 10.1007/s11336-011-9233-5
ISSN: 0033-3123
Abstract: This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under the three-parameter logistic model, the JM estimator returns larger estimates than the WL estimator. Several implications of this result are outlined.
Abstractor: As Provided
Number of References: 13
Entry Date: 2012
Accession Number: EJ951512
Database: ERIC
Description
Abstract:This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under the three-parameter logistic model, the JM estimator returns larger estimates than the WL estimator. Several implications of this result are outlined.
ISSN:0033-3123
DOI:10.1007/s11336-011-9233-5