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Computer-aided multivariate analysis / Abdelmonem Afifi, Virginia A. Clark and Susanne May.

By: Afifi, A. A. (Abdelmonem A.), 1939-.
Contributor(s): Clark, Virginia, 1928- | May, Susanne.
Material type: materialTypeLabelBookPublisher: Boca Raton : Chapman & Hall/CRC, 2004Edition: 4th ed.Description: xvi, 489 p. : ill. ; 25 cm.ISBN: 1584883081.Subject(s): Multivariate analysis -- Data processingDDC classification: 519.535
Contents:
One: Preparation for analysis -- What is multivariate analysis? -- Characterizing data for analysis -- Preparing for data analysis -- Data screening and transformations -- Selecting appropriate analyses -- Two: Applied regression analysis -- Simple regression and correlation -- Multiple regression and correlation -- Variable selection in regression -- Special regression topics -- Three: Multivariate analysis -- Canonical correlation analysis -- Discriminant analysis -- Logistic regression -- Regression analysis with survival data -- Principal components analysis -- Factor analysis -- Cluster analysis -- Log-linear analysis.
Holdings
Item type Current library Call number Copy number Status Barcode
General lending MTU Bishopstown Library Lending 519.535 (Browse shelf(Opens below)) 1 Available 00096421
Total holds: 0

Enhanced descriptions from Syndetics:

Computer-Aided Multivariate Analysis, Fourth Edition enables researchers and students with limited mathematical backgrounds to understand the concepts underlying multivariate statistical analysis, perform analysis using statistical packages, and understand the output. New topics include Loess and Poisson regression, nominal and ordinal logistic regression, interpretation of interactions in logistic and survival analysis, and imputation for missing values. This book includes new exercises and references, and updated options in the latest versions of the statistical packages. All data sets and codebooks are available for download.

The authors explain the assumptions made in performing each analysis and test, how to determine if your data meets those assumptions, and what to do if they do not. What to Watch out for sections in each chapter warn of common difficulties. By reading this text, you will know what method to use with your data set, how to get the results, and how to interpret them and explain them to others.

New in the Fourth Edition:

Expanded explanation of checking for goodness of fit in logistic regression and survival analysis Kaplan-Meier estimates of survival curves, formal tests for comparing survival between groups, interactions and the use of time-dependent covariates in survival analysis Expanded discussion of how to handle missing values Latest features of the S-PLUS package in addition to SAS, SPSS, STATA, and STATISTICA for multivariate analysis Data sets for the problems are available at the CRC web site: http://www.crcpress.com/product/isbn/9781584883081 Commands and output for examples used in the text for each statistical package are available at the UCLA web site: http://www.ats.ucla.edu/stat/examples/cama4/

Includes bibliographical references and index.

One: Preparation for analysis -- What is multivariate analysis? -- Characterizing data for analysis -- Preparing for data analysis -- Data screening and transformations -- Selecting appropriate analyses -- Two: Applied regression analysis -- Simple regression and correlation -- Multiple regression and correlation -- Variable selection in regression -- Special regression topics -- Three: Multivariate analysis -- Canonical correlation analysis -- Discriminant analysis -- Logistic regression -- Regression analysis with survival data -- Principal components analysis -- Factor analysis -- Cluster analysis -- Log-linear analysis.

Table of contents provided by Syndetics

  • Preface (p. xiii)
  • 1 Preparation for Analysis (p. 1)
  • 1 What is multivariate analysis? (p. 3)
  • 2 Characterizing data for analysis (p. 13)
  • 3 Preparing for data analysis (p. 23)
  • 4 Data screening and transformations (p. 49)
  • 5 Selecting appropriate analyses (p. 71)
  • 2 Applied Regression Analysis (p. 83)
  • 6 Simple regression and correlation (p. 85)
  • 7 Multiple regression and correlation (p. 125)
  • 8 Variable selection in regression (p. 165)
  • 9 Special regression topics (p. 197)
  • 3 Multivariate Analysis (p. 231)
  • 10 Canonical correlation analysis (p. 233)
  • 11 Discriminant analysis (p. 249)
  • 12 Logistic regression (p. 281)
  • 13 Regression analysis with survival data (p. 333)
  • 14 Principal components analysis (p. 369)
  • 15 Factor analysis (p. 391)
  • 16 Cluster analysis (p. 417)
  • 17 Log-linear analysis (p. 445)
  • Appendix A (p. 477)
  • A.1 Data sets and how to obtain them (p. 477)
  • A.2 Chemical companies financial data (p. 477)
  • A.3 Depression study data (p. 477)
  • A.4 Financial performance cluster analysis data (p. 478)
  • A.5 Lung cancer survival data (p. 478)
  • A.6 Lung function data (p. 478)
  • A.7 Parental HIV data (p. 479)
  • Index (p. 481)

Author notes provided by Syndetics

Abdelmonem Afifi is a Professor in the Department of Biostatistics at the University of California, Los Angeles
Virginia A. Clark is a consultant in Sequim, Washington
Susanne May is with the Department of Biostatistics at the University of California, San Diego