TY  - JOUR
AB  - Researchers decompose test score “gaps” and gap-changes into within- and between-school portions to generate evidence on the role that schools play in shaping educational inequality.  However, existing decomposition methods (a) assume an equal-interval test scale and (b) are a poor fit to coarsened data such as proficiency categories. We develop two decomposition approaches that overcome these limitations: an extension of V, an ordinal gap statistic (Ho, 2009), and an extension of ordered probit models (Reardon et al., 2017). Simulations show V decompositions have negligible bias with small within-school samples. Ordered probit decompositions have negligible bias with large within-school samples but more serious bias with small within-school samples. These methods are applicable to decomposing any ordinal outcome by any categorical grouping variable.
AU  - Quinn, David M.
AU  - Ho, Andrew D.
DA  - July 2020
DO  - 10.26300/3n9n-1c85
PY  - 2020
ST  - Ordinal Approaches to Decomposing Between-group Test Score Disparities
T2  - EdWorkingPapers.com
TI  - Ordinal Approaches to Decomposing Between-group Test Score Disparities
UR  - https://www.edworkingpapers.com/ai20-257
ID  - 230
ER  -