Practical Multivariate Analysis, Fifth Edition

Practical Multivariate Analysis, Fifth Edition
Author :
Publisher : CRC Press
Total Pages : 540
Release :
ISBN-10 : 9781439816806
ISBN-13 : 1439816808
Rating : 4/5 (808 Downloads)

Book Synopsis Practical Multivariate Analysis, Fifth Edition by : Abdelmonem Afifi

Download or read book Practical Multivariate Analysis, Fifth Edition written by Abdelmonem Afifi and published by CRC Press. This book was released on 2011-07-05 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Edition Chapter 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 and CRC Press Online.


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