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Robust Analysis of a Nonlinear Model for Multilevel Educational Survey Data

Author

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  • Dalia Rachman-Moore
  • Richard G. Wolfe

Abstract

A statistical model is proposed that describes the determination of an educational outcome variable as a nonlinear function of explanatory variables defined at different levels of a survey data hierarchy, say students and classes. The model hypothesizes that the student-level explanatory variables form a composite such that the intercept and slope in the regression of the outcome on the composite vary across classes systematically as functions of class-level variables and aggregates. A method is described for estimating the parameters of the model using robust techniques. The theoretical and practical derivation of the model is discussed, and an example is given.

Suggested Citation

  • Dalia Rachman-Moore & Richard G. Wolfe, 1984. "Robust Analysis of a Nonlinear Model for Multilevel Educational Survey Data," Journal of Educational and Behavioral Statistics, , vol. 9(4), pages 277-293, December.
    • Handle: RePEc:sae:jedbes:v:9:y:1984:i:4:p:277-293
    DOI: 10.3102/10769986009004277
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