Cover; Applying Generalizability Theory using EduG; Copyright; Contents; Foreword; Preface; Acknowledgments; Chapter 1 : What is generalizability theory?; Chapter 2 : Generalizability theory: Concepts and principles; Chapter 3 : Using EduG: The generalizability theory software; Chapter 4 : Applications to the behavioral and social sciences; Chapter 5 : Practice exercises; Chapter 6 : Current developments and future possibilities; Appendix A : Introduction to the analysis of variance; Appendix B : Sums of squares for unbalanced nested designs
Appendix C : Coef_G as a link between ˆ r2 and wˆ 2Appendix D : Confidence intervals for a mean or difference in means; Keyterms; References; Author index; Subject index
Summary
Intended to help improve measurement and data collection methods in the behavioral, social, and medical sciences, this book demonstrates an expanded and accessible use of Generalizability Theory (G theory). G theory conceptually models the way in which the reliability of measurement is ascertained. Sources of score variation are identified as potential contributors to measurement error and taken into account accordingly. The authors demonstrate the powerful potential of G theory by showing how to improve the quality of any kind of measurement, regardless of the discipline. Readers wi
Bibliography
Includes bibliographical references (pages 201-205) and indexes
