Reading and Understanding More Multivariate Statistics

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 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. 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.