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Improving the Crossing-SIBTEST Statistic for Detecting Non-uniform DIF

Published online by Cambridge University Press:  01 January 2025

R. Philip Chalmers
R. Philip Chalmers*
Affiliation:
Department of Educational Psychology, The University of Georgia
*
Correspondence should be made to R. Philip Chalmers, Department of Educational Psychology, The University of Georgia, 323 Aderhold Hall, Athens, GA 30602 USA. Email: rphilip.chalmers@uga.edu
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Abstract

This paper demonstrates that, after applying a simple modification to Li and Stout’s (Psychometrika 61(4):647–677, 1996) CSIBTEST statistic, an improved variant of the statistic could be realized. It is shown that this modified version of CSIBTEST has a more direct association with the SIBTEST statistic presented by Shealy and Stout (Psychometrika 58(2):159–194, 1993). In particular, the asymptotic sampling distributions and general interpretation of the effect size estimates are the same for SIBTEST and the new CSIBTEST. Given the more natural connection to SIBTEST, it is shown that Li and Stout’s hypothesis testing approach is insufficient for CSIBTEST; thus, an improved hypothesis testing procedure is required. Based on the presented arguments, a new chi-squared-based hypothesis testing approach is proposed for the modified CSIBTEST statistic. Positive results from a modest Monte Carlo simulation study strongly suggest the original CSIBTEST procedure and randomization hypothesis testing approach should be replaced by the modified statistic and hypothesis testing method.

Keywords

DIFnon-uniform DIFbidirectional biasSIBTESTCrossing-SIBTEST

Information

Type
Original Paper
Information
Psychometrika , Volume 83 , Issue 2 , June 2018, pp. 376 - 386
Copyright
Copyright © 2017 The Psychometric Society

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Footnotes

Special thanks to two anonymous reviewers for providing insightful comments that improved the quality of this manuscript. Correspondence concerning this article should be addressed to R. Philip Chalmers.

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