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Related Experiment Videos

Models for Value-Added Modeling of Teacher Effects.

Daniel F McCaffrey¹, J R Lockwood, Daniel Koretz

¹RAND.

Journal of Educational and Behavioral Statistics : a Quarterly Publication Sponsored by the American Educational Research Association and the American Statistical Association

|September 17, 2009

Summary

Complex value-added models evaluate teacher and school impact on student growth. A proposed mixed-model offers a robust framework, but student characteristics can confound results in diverse school populations.

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Area of Science:

Educational Measurement and Statistics
Longitudinal Data Analysis
Multivariate Statistics

Background:

Increasing use of complex value-added models (VAMs) to assess teacher and school contributions to student development.
Policy interest in VAMs for accountability and evaluation purposes.
Need for sophisticated statistical approaches to handle longitudinal student data nested within teachers and schools.

Purpose of the Study:

To present a general multivariate, longitudinal mixed-model for analyzing student data linked to teachers.
To demonstrate how existing VAM approaches are special cases of the proposed model.
To explore extensions for more complex data structures and investigate model misspecification impacts.

Main Methods:

Development of a general multivariate, longitudinal mixed-model.
Summarization and comparison of principal existing modeling approaches.
Simulation and analytical studies to examine teacher effects and model misspecifications.

Main Results:

The proposed mixed-model framework encompasses various existing VAM approaches.
Mixed models accounting for student correlation over time are robust to certain misspecifications when schools have similar student populations.
Estimated teacher effects can be confounded by student characteristics in schools with diverse student populations.

Conclusions:

The proposed mixed-model provides a flexible framework for VAMs in educational research.
Model robustness is contingent on the homogeneity of student populations across schools.
Careful consideration of student characteristics is crucial when interpreting teacher effects in VAMs, especially in heterogeneous school settings.