Latent Variable Regression Four-Level Hierarchical Model Using Multisite Multiple-Cohort Longitudinal Data

This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4...

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Bibliographic Details
Published inJournal of educational and behavioral statistics Vol. 44; no. 5; pp. 597 - 624
Main Authors Choi, Kilchan, Kim, Jinok
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publishing 01.10.2019
SAGE Publications
American Educational Research Association
Subjects
Academic Achievement
Achievement Tests
Bayesian analysis
Bayesian Statistics
Cohort Analysis
Computation
Educational Legislation
Elementary School Students
Federal Legislation
Grade 3
Grade 5
Growth Models
Hierarchical Linear Modeling
Longitudinal Studies
Low Income Students
Regression (Statistics)
Schools
Standardized Tests
Student Development
Students
distribution of student growth
hierarchical linear model
monitoring school performance
multiple cohort longitudinal data
fully Bayesian approach
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Summary:This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of change, arising from individual student over grades, and successive cohorts in the same grade over years. In addition, as an extension of Choi and Seltzer, the LVR coefficients, that is, gapin-time parameter, capturing the relationships between initial status and rates of changes within each cohort and school, help bring to light the distribution of student growth and differences in the distribution over different cohorts within schools. Advantages associated with the LVR-HM4 can be highlighted in studies on monitoring school performance or evaluations of policies and practices that may target different aspects of student academic performance such as initial status, growth, or gap over time in schools.
ISSN:1076-9986
1935-1054
DOI:10.3102/1076998619864538