Leveraging Federal Data in Education Research: Engaging With Administrative and Complex Sample Data

Session Type: Symposium

Abstract

Whether collected for statistical or administrative purposes, education researchers can use Federal data to examine relationships and evaluate programs. Researchers should be aware of certain caveats when using these datasets, such as the effect of complex sampling strategies or the regulatory context of data collection. In this session, the presenters will examine specific issues that arise when applying advanced analytic techniques to complex sample data, including best practices in application and reporting, the use of propensity score methods to estimate treatment effects, and a comparison of weighting methods for longitudinal data. The session will also include a presentation on recent policy initiatives to increase access to Federal administrative data for statistical purposes.

Sub Unit

• Division D - Measurement and Research Methodologies / Division D - Section 2: Quantitative Methods and Statistical Theory

Chair

• Deanne W. Swan, National Center for Education Statistics

Papers

• Challenges, Best Practices, and Innovations in Complex Sample Data Analysis - Debbie L. Hahs-Vaughn, University of Central Florida

• Combining Propensity Score Methods and Complex Survey Data to Estimate Population Treatment Effects - Elizabeth Stuart, Johns Hopkins University; Nianbo Dong, University of Missouri - Columbia

• Choice of Sampling Weight for Longitudinal Modeling of Panel Data - Laura M. Stapleton, University of Maryland - College Park; Jeffrey R. Harring, University of Maryland; Daniel Y Lee, University of Maryland - College Park

• Widening the Lens: Using Federal Administrative Data as a Resource in Education Research - Deanne W. Swan, National Center for Education Statistics

Discussant

• Gail M. Mulligan, NCES, Department of Education