Modeling Educational Inequalities at the Intersection of Multiple Social Categories: Introducing a Novel Multilevel Approach

• In Event: Hierarchical Linear Models

Abstract

Intersectional approaches have become increasingly important for explaining educational inequalities. This paper introduces the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach, a novel intersectional approach from epidemiology, to study educational inequalities. MAIHDA uses a multilevel model as the statistical framework to define intersectional strata that represent individuals’ membership in multiple social categories. By partitioning the variance within and between intersectional strata, the approach allows identifying intersectional effects at the strata level as well as obtaining information on the discriminatory accuracy of these strata for predicting individual educational outcomes. We illustrate the approach by analyzing inequalities in reading achievement using data from 15-year-old students in Germany (N = 5,451).

Authors

• Lena Keller, University of Potsdam
  Presenting Author

• Oliver Lüdtke, Leibniz Institute for Science and Mathematics Education
  Non-Presenting Author

• Franzis Preckel, University of Trier
  Non-Presenting Author

• Martin Brunner, University of Potsdam
  Non-Presenting Author