Estimating Achievement Gaps From Test Scores Reported in Ordinal “Proficiency†Categories

Andrew D. Ho and Sean F. Reardon
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Andrew D. Ho: Harvard Graduate School of Education
Sean F. Reardon: Stanford University

Journal of Educational and Behavioral Statistics, 2012, vol. 37, issue 4, 489-517

Abstract: Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This article introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered categories alone. These methods hold two practical advantages over alternative achievement gap metrics. First, they require only categorical proficiency data, which are often available where means and standard deviations are not. Second, they result in gap estimates that are invariant to score scale transformations, providing a stronger basis for achievement gap comparisons over time and across jurisdictions. The authors find three candidate estimation methods that recover full-distribution gap estimates well when only censored data are available.

Keywords: achievement gaps; proficiency; nonparametric statistics; ordinal statistics (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:37:y:2012:i:4:p:489-517

DOI: 10.3102/1076998611411918

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