Factor Analysis at 100: Historical Developments and Future Directions
| PUBLISHER | Routledge (03/06/2007) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
This book provides a retrospective look at major developments as well as a prospective view of future directions in factor analysis. 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. 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. Intended for 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.
Show More
Product Format
Product Details
ISBN-13:
9780805853476
ISBN-10:
0805853472
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
396
Carton Quantity:
18
Product Dimensions:
6.41 x 1.03 x 9.07 inches
Weight:
1.42 pound(s)
Feature Codes:
Bibliography,
Index,
Table of Contents,
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Medical | Biostatistics
Medical | Statistics
Medical | Statistics
Dewey Decimal:
150.287
Library of Congress Control Number:
2006015919
Descriptions, Reviews, Etc.
publisher marketing
This book provides a retrospective look at major developments as well as a prospective view of future directions in factor analysis. 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. 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. Intended for 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.
Show More
Editor:
MacCallum, Robert C.
Robert C. MacCallum, Ph.D. has had a long and distinguished career as a respected quantitative psychologist. His primary research interests involve the study of quantitative models and methods for the study of correlational data, especially factor analysis, structural equation modeling, and multilevel modeling. Of particular interest is the use of such methods for the analysis of longitudinal data, with a focus on individual differences in patterns of change over time. He teaches courses in factor analysis and introductory and advanced structural equation modeling. He currently serves as the program chair of the L. L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill.
Show More
List Price $190.00
Your Price
$188.10