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Maximizing Power in Generalizability Studies Under Budget Constraints

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  • George A. Marcoulides

Abstract

Generalizability theory provides a framework for examining the dependability of behavioral measurements. When designing generalizability studies, two important statistical issues are generally considered: power and measurement error. Control over power and error of measurement can be obtained by manipulation of sample size and/or test reliability. In generalizability theory, the mean error variance is an estimate that takes into account both these statistical issues. When limited resources are available, determining an optimal measurement design is not a simple task. This article presents a methodology for minimizing mean error variance in generalizability studies when resource constraints are imposed.

Suggested Citation

  • George A. Marcoulides, 1993. "Maximizing Power in Generalizability Studies Under Budget Constraints," Journal of Educational and Behavioral Statistics, , vol. 18(2), pages 197-206, June.
    • Handle: RePEc:sae:jedbes:v:18:y:1993:i:2:p:197-206
    DOI: 10.3102/10769986018002197
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    Cited by:

    1. Konstantopoulos, Spyros, 2008. "Incorporating Cost in Power Analysis for Three-Level Cluster Randomized Designs," IZA Discussion Papers 3753, Institute of Labor Economics (IZA).

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