Factor analysis is one of the success stories of statistics in the social sciences. It provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. This book demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Editor(s): Cudeck, Robert; MacCallum, Robert Charles. Num Pages: 400 pages, illustrations. BIC Classification: JHBC; JN; PBT. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 225 x 154 x 22. Weight in Grams: 540. . 2007. 1st Edition. paperback. . . . .

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Bibliographic Details

Title: Factor Analysis at 100: Historical Developments and Future Directions
Publisher: Routledge
Publication Date: 2007
Language: English
ISBN 10: 0805862129
ISBN 13: 9780805862126
Binding: Soft cover
Edition: 1st Edition
Condition: New

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Synopsis

Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Because of its importance, a conference was held to mark the centennial of the publication of Charles Spearman's seminal 1904 article which introduced the major elements of this invaluable statistical tool. This book evolved from that conference. It provides a retrospective look at major issues and developments as well as a prospective view of future directions in factor analysis and related methods. In so doing, it demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Featuring an outstanding collection of contributors, this volume offers unique insights on factor analysis and its related methods. Several chapters have a clear historical perspective, while others present new ideas along with historical summaries. In addition, the book reviews some of the extensions of factor analysis to such techniques as latent growth curve models, models for categorical data, and structural equation models. Factor Analysis at 100 will appeal to graduate students and researchers in the behavioral, social, health, and biological sciences who use this technique in their research. A basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.

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Robert Cudeck and Robert C. MacCallum

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