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Generalizability Theory

'Statistics for Social Science and Public Policy'. Auflage 2001. Book. Sprache: Englisch.
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Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. It liberalizes classical test theory, in part through the application of... weiterlesen
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Produktdetails
Titel: Generalizability Theory
Autor/en: Robert L. Brennan

ISBN: 0387952829
EAN: 9780387952826
'Statistics for Social Science and Public Policy'.
Auflage 2001.
Book.
Sprache: Englisch.
Springer New York

9. August 2001 - gebunden - 564 Seiten

Beschreibung

Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. It liberalizes classical test theory, in part through the application of analysis of variance procedures that focus on variance components. As such, generalizability theory is perhaps the most broadly defined measurement model currently in existence. It is applicable to virtually any scientific field that attends to measurements and their errors, and it enables a multifacteted perspective on measurement error and its components. This book provides the most comprehensive and up-to-date treatment of generalizability theory. In addition, it provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory. The principal intended audience is measurement practitioners and graduate students in the behavioral and social sciences, although a few examples and references are provided from other fields. Readers will benefit from some familiarity with classical test theory and analysis of variance, but the treatment of most topics does not presume specific background. Robert L. Brennan is E.F. Lindquist Professor of Educational Measurement at the University of Iowa. He is an acknowledged expert in generalizability theory, has authored numerous publications on the theory, and has taught many courses and workshops on generalizability. The author has been Vice-President of the American Educational Research Association and President of the National Council on Measurement in Education (NCME). He has received NCME Awards for Outstanding Technical Contributions to Educational Measurement and Career Contributions to Educational Measurement.

Inhaltsverzeichnis

Introduction * Single-facet Designs * Multifacet Universes of Admissible Observations and G Study Designs * Multifacet Universes of Generalization and D Study Designs * Advanced Topics in Univariate Generalizability Theory * Variability of Statistics in Generalizability Theory * Unbalanced Random Effects Designs * Unbalanced Random Effects Designs--Examples * Multivariate G Studies * Multivariate D Studies * Multivariate Regressed Scores

Pressestimmen

From the reviews:
The book provides a comprehensive and up-to-date treatment of generalizability theory. It provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory." Mathematical Reviews
"...This book belongs in every measurement specialist's reference collection, as a resource to which to turn for insight into virtually any question about GT, whether it deals with univariate or multivariate applications. There is simply nowhere else to get such a comprehensive presentation of the theory." Psychometrika
"This book fills a need for up-to-date presentation, critical review, and analysis of issues in generalizability theory, particularly in multivariate generalizability theory. Brennan has for many years been at the forefront of research and development in generalizability theory and he provides a well-written, thoughtful, focused analysis of recent issues. I would highly recommend this book to anyone seriously interested in learning about generalizability theory. It is an excellent resource for anyone wanting to use generalizability theory in research ... ." (Laura L. B. Barnes, Journal of Education Measurement, 2002)

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