Implications of Socioeconomic Status Modeling in International Large-Scale Assessments

• In Event: AERA Poster Session Wednesday 7:45am
  In Poster Session: Insights from Large-Scale Assessments: Advancing Methods, Measurement, and Learning Opportunities

Abstract

This study explores the impact of modeling choices on the measurement of socioeconomic status (SES) in International Large-Scale Assessments (ILSAs), focusing on the Estudio Regional Comparativo y Explicativo (ERCE). It compares formative and reflective approaches, using Principal Component Analysis (PCA) and Factor Analysis (FA), respectively. Results indicate that reflective models inflate estimates due to assumptions about measurement error, while formative models yield attenuated estimates. Discrepancies in estimates concentrate on a few SES items, particularly parental education and occupation. These discrepancies vary by country, with smaller countries showing greater item commonalities and thus larger FA-PCA differences. The findings underline the necessity of aligning modeling strategies with theoretical assumptions to enhance the validity and cross-country comparability of SES constructs in ILSAs.

Author

• Andres Fernandez-Vergara, University of California - Los Angeles