Efficient standard error formulas of ability estimators with dichotomous item response models

[en] This paper focuses on the computation of asymptotic standard errors (ASE) of ability estimators with dichotomous item response models. A general framework is considered and ability estimators are defined from a very restricted set of assumptions and formulas. This approach encompasses most standard methods such as maximum likelihood, weighted likelihood, maximum a posteriori and robust estimators. A general formula for the ASE is derived from the theory of M-estimation. Well-known results are found back as particular cases for the maximum and robust estimators, while new ASE proposals for the weighted likelihood and maximum a posteriori estimators are presented. These new formulas are compared to traditional ones by means of a simulation study under Rasch modeling.

Disciplines :

Education & instruction

Author, co-author :

Magis, David ; Université de Liège - ULiège > Département Education et formation > Psychométrie et édumétrie

Language :

English

Title :

Efficient standard error formulas of ability estimators with dichotomous item response models

Publication date :

2016

Journal title :

Psychometrika

ISSN :

0033-3123

eISSN :

1860-0980

Publisher :

Psychonomic Society, Research Triangle Park, United States - Virginia

Volume :

Pages :

184-200

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 29 January 2015

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