Since 1995, over 13,000 graduate students and researchers have relied on Reading and Understanding Multivariate Statistics for a basic understanding of the most commonly used multivariate analyses in the research literature today. In Reading and Understanding MORE Multivariate Statistics, the editors have responded to reader requests to provide the same accessible approach to a new group of multivariate techniques and related topics in measurement. Chapters demystify the use of cluster analysis, Q-technique factor analysis, structural equation modeling, canonical correlation analysis, repeated measures analyses, and survival analysis.

As with the previous volume, chapter authors describe the research questions for which the statistic is most appropriate, the underlying assumptions and rationale of the analysis, and the logic behind interpreting the results. Designed to clarify each statistic's logic and utility rather than teach hands-on application, the book emphasizes the real-world use of statistical methods with minimal reliance on complex mathematical formulas. Each chapter contains accessible discussions of general principles, instructions for interpreting summary tables, and a glossary of key terms and statistical notations. Whether you are a graduate student, researcher, or consumer of research, this volume is guaranteed to increase your comfort level and confidence in reading and understanding multivariate statistics.

Table of Contents




  1. Introduction to Multivariate Statistics
    —Laurence G. Grimm and Paul R. Yarnold
  2. Reliability and Generalizability Theory
    —Michael J. Strube
  3. Item Response Theory
    —David H. Henard
  4. Assessing the Validity of Measurement
    —Fred B. Bryant
  5. Cluster Analysis
    —Joseph F. Hair Jr. and William C. Black
  6. Q-Technique Factor Analysis: One Variation on the Two-Mode Factor Analysis of Variables
    —Bruce Thompson
  7. Structural Equation Modeling
    —Laura Klem
  8. Ten Commandments of Structural Equation Modeling
    —Bruce Thompson
  9. Canonical Correlation Analysis
    —Bruce Thompson
  10. Repeated Measures Analyses: ANOVA, MANOVA, and HLM
    —Kevin P. Weinfurt
  11. Survival Analysis
    —Raymond E. Wright


About the Editors

Reviews & Awards

This very useful and easy-to-use book presents the basic and fundamental concepts of multivariate statistical techniques and measurement topics using simple and intuitive arguments, relying on as little mathematics and as few equations as possible. The contributing authors and the editors have done an excellent job in keeping the theme and spirit of this volume intact from page to page.
—CHOICE Magazine