The asymptotic posterior normality of the latent trait in an IRT model

Hua Hua Chang; William Stout

doi:10.1007/BF02294469

The asymptotic posterior normality of the latent trait in an IRT model

Research output: Contribution to journal › Article › peer-review

Abstract

It has long been part of the item response theory (IRT) folklore that under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test. Under very general and nonrestrictive nonparametric assumptions, we make this claim rigorous for a broad class of latent models.

Original language	English (US)
Pages (from-to)	37-52
Number of pages	16
Journal	Psychometrika
Volume	58
Issue number	1
DOIs	https://doi.org/10.1007/BF02294469
State	Published - Mar 1993
Externally published	Yes

Keywords

ability estimation
confidence interval
Dutch Identity
empirical Bayes
item response theory
manifest probably
posterior distribution

ASJC Scopus subject areas

Social Sciences (miscellaneous)
Psychology (miscellaneous)
General Psychology
Mathematics (miscellaneous)

Online availability

10.1007/BF02294469

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The asymptotic posterior normality of the latent trait in an IRT model

Abstract

Keywords

ASJC Scopus subject areas

Online availability

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