A stepwise test characteristic curve method to detect item parameter drift

Guo, Rui

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https://hdl.handle.net/2142/49806 Copy

Description

Title

A stepwise test characteristic curve method to detect item parameter drift

Author(s)

Guo, Rui

Issue Date

2014-05-30T17:18:39Z

Director of Research (if dissertation) or Advisor (if thesis)

Chang, Hua-Hua

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.A.

Degree Level

Thesis

Keyword(s)

• item parameter drift
• stepwise selection
• test characteristic curve
• item response theory
• true score equating

Abstract

An important assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several methods have been proposed to detect drifted items. However, most of the existing methods aim at detecting the drift in individual items, which may not be ideal when only the overall test characteristic curve (TCC) is of interest to the users. One such occasion in common practice is IRT-based true score equating, where the goal is to create a conversion table to make the two TCCs as close as possible. This paper introduces a stepwise test characteristic curve (Stepwise TCC) method to dynamically detect item parameter drift based on TCC without requirement to set any critical values. Comparisons were made between the new method and two commonly used existing methods under the three-parameter logistic model. Results show that the new method performed well in IPD detection.

Graduation Semester

2014-05

Permalink

http://hdl.handle.net/2142/49806

Copyright and License Information

Copyright 2014 Rui Guo

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