Practical Multivariate Analysis (6^th Ed.) Chapman & Hall/CRC Texts in Statistical Science Series

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians.

Key Features:

• Provides a comprehensive, practical and accessible introduction to multivariate analysis.
• Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience.
• Includes lots of detailed worked examples, guidance on computing, and exercises.
• Updated with a new chapter on data visualization.

Part I: Preparation for Analysis. What is Multivariate Analysis? Characterizing Data for Analysis. Preparing for Data Analysis. Data Visualization. Data Screening and Transformations. Data Visualization. Selecting Appropriate Analyses. Part II: Regression Analysis. Simple Regression and Correlation. Multiple Regression and Correlation. Variable Selection in Regression. Special Regression Topics. Discriminant analysis. Logistic Regression. Regression Analysis with Survival Data. Principal Components Analysis. Factor Analysis. Cluster Analysis. Log-Linear Analysis. Correlated Outcomes Regression.

Abdelmonem Afifi, Ph.D., has been Professor of Biostatistics in the School of Public Health, University of California, Los Angeles (UCLA) since 1965, and served as the Dean of the School from 1985 until 2000. His research includes multivariate and multilevel data analysis, handling missing observations in regression and discriminant analyses, meta-analysis, and model selection. Over the years, he taught well-attended courses in biostatistics for Public Health students and clinical research physicians, and doctoral-level courses in multivariate statistics and multilevel modeling. He has authored many publications in statistics and health related fields, including two widely used books (with multiple editions) on multivariate analysis. He received several prestigious awards for excellence in teaching and research.

Susanne May, Ph.D., is a Professor in the Department of Biostatistics at the University of Washington in Seattle. Her areas of expertise and interest include clinical trials, survival analysis, and longitudinal data analysis. She has more than 20 years of experience as a statistical collaborator and consultant on health related research projects. In addition to a number of methodological and applied publications, she is a coauthor (with Drs. Hosmer and Lemeshow) of Applied Survival Analysis: Regression Modeling of Time-to-Event Data. Dr. May has taught courses on introductory statistics, clinical trials, and survival analysis.

Robin A. Donatello, Dr. P.H., is an Associate Professor in the Department of Mathematics and Statistics and the Developer of the Data Science Initiative at California State University, Chico. Her areas of interest include applied research in the Public Health and Natural Science fields. She has expertise in data visualization, techniques to address missing and erroneous data, implementing reproducible research workflows, computational statistics and Data Science. Dr. Do