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Locally Dependent Latent Trait Model and the Dutch Identity Revisited

Published online by Cambridge University Press:  01 January 2025

Edward H. Ip
Edward H. Ip*
Affiliation:
Marshall School of Business, University of Southern California
*
Requests for reprints should be sent to Edward Ip, Information and Operations Management, Marshall School of Business, University of Southern California, Los Angeles, CA 90089. E-Mail: eddie.ip@marshall.usc.edu
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Abstract

In this paper, we propose a class of locally dependent latent trait models for responses to psychological and educational tests. Typically, item response models treat an individual's multiple response to stimuli as conditional independent given the individual's latent trait. In this paper, instead the focus is on models based on a family of conditional distributions, or kernel, that describes joint multiple item responses as a function of student latent trait, not assuming conditional independence. Specifically, we examine a hybrid kernel which comprises a component for one-way item response functions and a component for conditional associations between items given latent traits. The class of models allows the extension of item response theory to cover some new and innovative applications in psychological and educational research. An EM algorithm for marginal maximum likelihood of the hybrid kernel model is proposed. Furthermore, we delineate the relationship of the class of locally dependent models and the log-linear model by revisiting the Dutch identity (Holland, 1990).

Keywords

hybrid kernelEM algorithmgeneralized log-linear modelreproducibility

Information

Type
Articles
Information
Psychometrika , Volume 67 , Issue 3 , September 2002 , pp. 367 - 386
Copyright
Copyright © 2002 The Psychometric Society

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Footnotes

The work is supported by a research grant from the Marshall School of Business, University of Southern California. The author thanks the anonymous referees for their suggestions.

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