School-level inequality measurement based categorical data: a novel approach applied to PISA

Sempé, Lucas (2021) School-level inequality measurement based categorical data: a novel approach applied to PISA. Large-Scale Assessments in Education, 9 (1). ISSN 2196-0739

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Abstract

This paper introduces a new method to measure school-level inequality based on Item Response Theory (IRT) models. Categorical data collected by large-scale assessments poses diverse methodological challenges hinder measuring inequality due to data truncation and asymmetric intervals between categories. I use family possessions data from PISA 2015 to exemplify the process of computing the measurement and develop a set of country-level mixed-effects linear regression models comparing the predictive performance of the novel inequality measure with school-level Gini coefficients. I find school-level inequality is negatively associated with learning outcomes across many non-European countries.

Item Type: Article
Uncontrolled Keywords: homepos,inequality,item response theory,ordinal data,pisa,school inequality,education ,/dk/atira/pure/subjectarea/asjc/3300/3304
Faculty \ School: Faculty of Social Sciences > School of International Development
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 08 Oct 2021 00:56
Last Modified: 20 Oct 2021 03:27
URI: https://ueaeprints.uea.ac.uk/id/eprint/81609
DOI: 10.1186/s40536-021-00103-7

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