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A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment

Published online by Cambridge University Press:  01 January 2025

Kei Miyazaki
Affiliation:
Department of Cognitive and Behavioral Science, The University of Tokyo
Takahiro Hoshino*
Affiliation:
Graduate School of Economics, Nagoya University
Shin-ichi Mayekawa
Affiliation:
Graduate School of Decision Science and Technology, Tokyo Institute of Technology
Kazuo Shigemasu
Affiliation:
Department of Cognitive and Behavioral Science, The University of Tokyo
*
Requests for reprints should be sent to Takahiro Hoshino, Graduate School of Economics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan. E-mail: bayesian@jasmine.ocn.ne.jp

Abstract

This study proposes a new item parameter linking method for the common-item nonequivalent groups design in item response theory (IRT). Previous studies assumed that examinees are randomly assigned to either test form. However, examinees can frequently select their own test forms and tests often differ according to examinees’ abilities. In such cases, concurrent calibration or multiple group IRT modeling without modeling test form selection behavior can yield severely biased results. We proposed a model wherein test form selection behavior depends on test scores and used a Monte Carlo expectation maximization (MCEM) algorithm. This method provided adequate estimates of testing parameters.

Information

Type
Theory and Methods
Copyright
Copyright © 2008 The Psychometric Society

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