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Estimating Achievement Gaps From Test Scores Reported in Ordinal “Proficiency” Categories
Author(s) -
Andrew Ho,
Sean F. Reardon
Publication year - 2011
Publication title -
journal of educational and behavioral statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.066
H-Index - 59
eISSN - 1935-1054
pISSN - 1076-9986
DOI - 10.3102/1076998611411918
Subject(s) - categorical variable , achievement test , metric (unit) , ordinal scale , ordinal data , econometrics , statistics , computer science , standardized test , mathematics , operations management , economics
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.

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