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In this volume, Shavelson and Webb offer an intuitive development of generalizability theory and cover a wide variety of topics such as generalizability studies with nested facets and with fixed facets, measurement error and generalizability coefficients, and decision studies with same and with different designs. Detailed illustrations, examples and exercises all serve to clearly describe the logic underlying major concepts in generalizability theory and assist readers in applying these methods when investigating the consistency of their own measurements.
This is a well-written, easy-to-digest book that I was able to read in two sittings over one weekend. It provides the background on G Theory, but if you're hoping to conduct your own G Study, you'll also need Brennan's "Generalizability Theory" and the GENOVA software that is free and available on the web.
It provides interpretations of the examples covered in the book. These interpretations help me understand G theory better and add depth in my own research papers.
Anyone doing large-scale, quantitative research should have this book. It introduces you to generalizatility theory and its purposes in the quantitative field.
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