Maximizing Power in Generalizability Studies Under Budget Constraints

George A. Marcoulides

Journal of Educational and Behavioral Statistics, 1993, vol. 18, issue 2, 197-206

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.

Keywords: generalizability theory; measurement error; power (search for similar items in EconPapers)
Date: 1993
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986018002197 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:18:y:1993:i:2:p:197-206

DOI: 10.3102/10769986018002197

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().