A Robust Test for Checking the Homogeneity of Variability Measures and Its Application to the Analysis of Implicit Attitudes

Ryan C. Erps and Kimihiro Noguchi
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Kimihiro Noguchi: Western Washington University

Journal of Educational and Behavioral Statistics, 2020, vol. 45, issue 4, 403-425

Abstract: A new two-sample test for comparing variability measures is proposed. To make the test robust and powerful, a new modified structural zero removal method is applied to the Brown–Forsythe transformation. The t -test-based statistic allows results to be expressed as the ratio of mean absolute deviations from median. Extensive simulation study demonstrates that the proposed test is robust to small or unequal sample sizes across many distributions. Moreover, careful exploratory analysis provides a new method for calculating the implicit association test scores for reaction time data with multiplicative treatment effects. Using this, a possible difference between variability of men and women’s implicit attitudes toward gay men is analyzed.

Keywords: Brown-Forsythe transformation; effect size; implicit association test (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:45:y:2020:i:4:p:403-425

DOI: 10.3102/1076998619883874

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