Validity Generalization (eBook, PDF)
A Critical Review
Redaktion: Murphy, Kevin R.
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This volume presents the first wide-ranging critical review of validity generalization (VG)--a method that has dominated the field since the publication of Schmidt and Hunter's (1977) paper "Development of a General Solution to the Problem of Validity Generalization." This paper and the work that followed had a profound impact on the science and practice of applied psychology. The research suggests that fundamental relationships among tests and criteria, and the constructs they represent are simpler and more regular than they appear. Looking at the history of the VG model and its impact on per...
This volume presents the first wide-ranging critical review of validity generalization (VG)--a method that has dominated the field since the publication of Schmidt and Hunter's (1977) paper "Development of a General Solution to the Problem of Validity Generalization." This paper and the work that followed had a profound impact on the science and practice of applied psychology. The research suggests that fundamental relationships among tests and criteria, and the constructs they represent are simpler and more regular than they appear.
Looking at the history of the VG model and its impact on personnel psychology, top scholars and leading researchers of the field review the accomplishments of the model, as well as the continuing controversies. Several chapters significantly extend the maximum likelihood estimation with existing models for meta analysis and VG. Reviewing 25 years of progress in the field, this volume shows how the model can be extended and applied to new problems and domains. This book will be important to researchers and graduate students in the areas of industrial organizational psychology and statistics.
Looking at the history of the VG model and its impact on personnel psychology, top scholars and leading researchers of the field review the accomplishments of the model, as well as the continuing controversies. Several chapters significantly extend the maximum likelihood estimation with existing models for meta analysis and VG. Reviewing 25 years of progress in the field, this volume shows how the model can be extended and applied to new problems and domains. This book will be important to researchers and graduate students in the areas of industrial organizational psychology and statistics.
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