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

Author

Listed:
  • Kilchan Choi
  • Jinok Kim

    (CRESST/UCLA)

Abstract

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, gap-in-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.

Suggested Citation

  • Kilchan Choi & Jinok Kim, 2019. "Latent Variable Regression Four-Level Hierarchical Model Using Multisite Multiple-Cohort Longitudinal Data," Journal of Educational and Behavioral Statistics, , vol. 44(5), pages 597-624, October.
    • Handle: RePEc:sae:jedbes:v:44:y:2019:i:5:p:597-624
    DOI: 10.3102/1076998619864538
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    References listed on IDEAS

    as
    1. George Leckie, 2009. "The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 537-554, June.
    2. George Leckie & Harvey Goldstein, 2009. "The limitations of using school league tables to inform school choice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 835-851, October.
    3. Kilchan Choi & Michael Seltzer, 2010. "Modeling Heterogeneity in Relationships Between Initial Status and Rates of Change: Treating Latent Variable Regression Coefficients as Random Coefficients in a Three-Level Hierarchical Model," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 54-91, February.
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