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DIFFERENTIAL ITEM FUNCTIONING AND ADVERSE IMPACT: A - csus-dspace calstate

DIFFERENTIAL ITEM FUNCTIONING AND ADVERSE IMPACT: A - csus-dspace calstate 2025

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The thesis by Heather JoAn Whiteman presents a comparative analysis of two methods for detecting differential item functioning (DIF) in a selection test taken by 29,171 applicants. The study evaluates the Mantel-Haenszel chi-square method and logistic regression, focusing on their impact on adverse impact when items displaying DIF are removed. Results indicate that the Mantel-Haenszel method identifies more instances of moderate or large DIF compared to logistic regression. However, both methods similarly reduce adverse impact across demographic groups. The findings suggest that while the Mantel-Haenszel method may detect more DIF, the logistic regression method retains more items and maintains higher test reliability. The study concludes that practical considerations such as cost and resource availability may influence the choice of method in applied settings.

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What is a differential item functioning?

Differential item functioning (DIF) is a term in psychometrics for the statistical analysis of assessment data to determine if items are performing in a biased manner against some group of examinees.

What is differential item functioning and health assessment?

Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale.

What is differential test function?

Differential Test Functioning DTF concerns the possibility that the measurement procedure, as a whole, does not perform the same for two groups, such as females and males.

What is dif and dtf?

DTF. ASWB, like most high-stakes exam developers, relies on DIF (differential item functioning) analysis to assess for measurement bias at the item (question) level, as opposed to DTF (differential test functioning) analysis, which assesses for measurement bias at the test level.