Reading and Understanding More Multivariate Statistics.

Grimm, Laurence G. (editor); Yarnold, Paul R. (editor).

ISBN 10: 1557986983 / ISBN 13: 9781557986986

Published by American Psychological Association (APA), Washington, DC, 2000

About this Item

Paperback thick quarto, very good plus condition, figures, tables, bottom edge little rubbed, minor edgewear. Heavy, and extra postage may be requested to destinations outside Australia. 437 pp. This book, edited by Laurence Grim and Paul Yarnold, and the second book in the series, presents fundamental conceptual aspects of additional multivariate techniques and measurement topics, and explains these procedures in simple, intuitive terms, using as few equations as possible. The author of each chapter provides example applications of each statistical analysis, the underlying assumptions and mechanics of the analysis, and a discussion of an interesting working example. Each chapter includes a glossary of terms and symbols that provides a quick way to access succinct definitions of fundamental concepts discussed in the text. For graduate students, this book may be a useful companion to the many standard texts that teach the students to perform multivariate analyses in statistics courses as preparation for doing their own research.

Seller Inventory # 18357

Bibliographic Details

• Title: Reading and Understanding More Multivariate Statistics.
• Publisher: American Psychological Association (APA), Washington, DC
• Publication Date: 2000
• Language: English
• ISBN 10: 1557986983
• ISBN 13: 9781557986986
• Binding: Soft cover
• Edition: 1st ed.
• Seller catalogs:
  • RESEARCH & STATISTICS

About this title

Synopsis

This follow up text to the editors' Reading and Understanding Multivariate Statistics applies the accessible approach of the previous work to a new group of multivariate techniques and to related topics in measurement. The text seeks to demystify the use of cluster analysis, Q-technique factor analysis, structural equation modeling, canonical correlation analysis, repeated measures analysis, and survival analysis. Research questions for which each analysis is most appropriate are described, and the underlying assumptions and rationale of the analysis, and the logic behind interpreting the results, are explained. Assumes an understanding of univariate statistics but no prior experience with multivariate statistics. Annotation c. Book News, Inc., Portland, OR (booknews.com)