Examining Subpopulation Trends Through the Pseudo-Panel Approach: A Methodology for Analyzing Large-Scale Assessment Data

• In Event: Novel Approaches to Large-Scale Assessment Data Analysis and Practice

Abstract

This paper illustrates an approach for analyzing large scale assessment data longitudinally. TIMSS, PIRLS, PISA, and NAEP assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Adapting a pseudo-panel approach from the econometrics literature (Deaton, 1985), the proposed approach creates subpopulations by grouping students based on demographic characteristics, such as gender or parental education. Following grouping, the subpopulations with the same demographic characteristics are linked across cycles and the aggregated subpopulation means are treated as panel data and analyzed through longitudinal data analysis techniques. As demonstrated herein a primary advantage of this subpopulation approach is that it allows for analysis of subgroup differences.

Author

• Martin Hooper, TIMSS & PIRLS International Study Center, Boston College