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Analyzing Multilevel Data in the Presence of Heterogeneous Within-Class Regressions

Author

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  • Leigh Burstein
  • Robert L. Linn
  • Frank J. Capell

Abstract

The concerns of this investigation are multiple sources of complications in the analysis of multilevel educational data. The focus is on problems that arise when within-group regressions of outcome on input are related to teacher/ school characteristics. Single-level and multilevel analytical approaches are applied to hypothetical data for which the relationship between teacher/class quality and the heterogeneity of within-class slopes is varied systematically. It is shown that single-level analyses and the proposed multilevel approaches can all yield mislèading estimates of teacher/class effects on mean class outcomes. However, selected multilevel methods provide some indication of misspecification and can identify the direction of the bias in estimating teacher/class effects on mean class outcomes.

Suggested Citation

  • Leigh Burstein & Robert L. Linn & Frank J. Capell, 1978. "Analyzing Multilevel Data in the Presence of Heterogeneous Within-Class Regressions," Journal of Educational and Behavioral Statistics, , vol. 3(4), pages 347-383, December.
    • Handle: RePEc:sae:jedbes:v:3:y:1978:i:4:p:347-383
    DOI: 10.3102/10769986003004347
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    Cited by:

    1. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
    2. Chen, Tzu-Ying & Jou, Rong-Chang, 2019. "Using HLM to investigate the relationship between traffic accident risk of private vehicles and public transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 148-161.

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