Afifi A., May S., Clark V.A. Practical Multivariate Analysis

5th Edition. — Hoboken: CRC Press, 2011. — 508 p. — (Texts in Statistical Science Series). — ISBN: 978-1-4665-0324-3.This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical analyses and understand the results. For each of the techniques presented in this edition, the authors use the most recent software versions available and discuss the most modern ways of performing the analysis.New to the Fifth EditionChapter on regression of correlated outcomes resulting from clustered or longitudinal samples
Reorganization of the chapter on data analysis preparation to reflect current software packages
Use of R statistical software
Updated and reorganized references and summary tables
Additional end-of-chapter problems and data sets
The first part of the book provides examples of studies requiring multivariate analysis techniques; discusses characterizing data for analysis, computer programs, data entry, data management, data clean-up, missing values, and transformations; and presents a rough guide to assist in choosing the appropriate multivariate analysis. The second part examines outliers and diagnostics in simple linear regression and looks at how multiple linear regression is employed in practice and as a foundation for understanding a variety of concepts. The final part deals with the core of multivariate analysis, covering canonical correlation, discriminant, logistic regression, survival, principal components, factor, cluster, and log-linear analyses.
While the text focuses on the use of R, S-PLUS, SAS, SPSS, Stata, and STATISTICA, other software packages can also be used since the output of most standard statistical programs is explained. Data sets and code are available for download from the book’s web page.Authors' BiographiesPreparation for AnalysisWhat is multivariate analysis?
Characterizing data for analysis
Preparing for data analysis
Data screening and transformations
Selecting appropriate analysesApplied Regression AnalysisSimple regression and correlation
Multiple regression and correlation
Variable selection in regression
Special regression topicsMultivariate AnalysisCanonical correlation analysis
Discriminant analysis
Logistic regression
Regression analysis with survival data
Principal components analysis
Factor analysis
Cluster analysis
Log-linear analysis
Correlated outcomes regression