Efficient Standard Error Formulas of Ability Estimators with Dichotomous Item Response Models

David Magis ()

Psychometrika, 2016, vol. 81, issue 1, 184-200

Abstract: 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. Copyright The Psychometric Society 2016

Keywords: item response theory; ability estimation; asymptotic standard error; maximum likelihood; weighted likelihood; Bayesian estimation; Robust estimation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:psycho:v:81:y:2016:i:1:p:184-200

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DOI: 10.1007/s11336-015-9443-3

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