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Recent advances in statistical methodology and computer automation are making canonical correlation analysis available to more and more researchers. This volume explains the basic features of this sophisticated technique in an essentially non-mathematical introduction which presents numerous examples. Thompson discusses the assumptions, logic, and significance testing procedures required by this analysis, noting trends in its use and some recently developed extensions.
"This is a book that should be on the desk of anyone truly concerned with reliability. The whole question of conditional reliabilities is current and important; and, the question of reliability generalization is being opened out and moving away from Cronbach's approach. The topic is an important one."--Richard L. Gorsuch, Director of Research in Graduate School of Psychology, Fuller Theological Seminary Should a high school diploma be awarded to students based on their score on a final exit exam? Should businesses deny employment to people based on their score on a personality test? In a world of "high stakes" testing, it has become more important than ever to make certain the scores on which we base our decisions are reliable. Aimed at helping researchers create and evaluate scores better, this reader presents the basic concepts of classical (or "true score") and modern ("generalizability") test theory. Beginning with a review of reliability and validity issues in measurement, the book covers score reliability, reliability induction, and reliability generalization. Exercises with sample data are included at the end of each section so readers can demonstrate knowledge of the principles.
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