MAXIMIZING POWER IN GENERALIZABILITY STUDIES UNDER BUDGET CONSTRAINTS

Generalizability theory provides a framework for examining the dependa bility of behavioral measurements. When designing generalizability stu dies, two important statistical issues are generally considered: power and measurement error. Control over power and error of measurement ca n be obtained by manipulation of sample size and/or test reliability. In generalizability theory, the mean error variance is an estimate tha t takes into account both these statistical issues. When limited resou rces 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 a re imposed.