Abstract
Measuring academic growth, or change in aptitude, relies on longitudinal data collected across multiple measurements. The National Educational Longitudinal Study (NELS:88) is among the earliest, large-scale, educational surveys tracking students’ performance on cognitive batteries over 3 years. Notable features of the NELS:88 data set, and of almost all repeated measures educational assessments, are (a) the outcome variables are binary or at least categorical in nature; and (b) a set of different items is given at each measurement occasion with a few anchor items to fix the measurement scale. This study focuses on the challenges related to specifying and fitting a second-order longitudinal model for binary outcomes, within both the item response theory and structural equation modeling frameworks. The distinctions between and commonalities shared between these two frameworks are discussed. A real data analysis using the NELS:88 data set is presented for illustration purposes.
Original language | English (US) |
---|---|
Pages (from-to) | 455-465 |
Number of pages | 11 |
Journal | Structural Equation Modeling |
Volume | 23 |
Issue number | 3 |
DOIs | |
State | Published - May 3 2016 |
Bibliographical note
Funding Information:National Academy of Education/Spencer Foundation
Publisher Copyright:
Copyright © Taylor & Francis Group, LLC.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
Keywords
- binary outcomes
- item response theory
- longitudinal
- structural equation modeling