Increasingly, researchers need to perform multivariate statistical analyses on their data. Unfortunately, a lack of mathematical training prevents many from taking advantage of these advanced techniques, in part, because books focus on the theory and neglect to explain how to perform and interpret multivariate analyses on real-life data.For years, Afifi and Clark's Computer-Aided Multivariate Analysis has been a welcome exception-helping researchers choose the appropriate analyses for their data, carry them out, and interpret the results. Only a limited knowledge of statistics is assumed, and geometrical and graphical explanations are used to explain what the analyses do. However, the basic model is always given, and assumptions are discussed.Reflecting the increased emphasis on computers, the Third Edition includes three additional statistical packages written for the personal computer. The authors also discuss data entry, database management, data screening, data transformations, as well as multivariate data analysis. Another new chapter focuses on log-linear analysis of multi-way frequency tables.Students in a wide range of fields-ranging from psychology, sociology, and physical sciences to public health and biomedical science-will find Computer-Aided Multivariate Analysis especially informative and enlightening.
Author(s): A. A. Afifi, V. Clark
Series: Chapman & Hall Texts in Statistical Science Series
Edition: 3
Publisher: Chapman & Hall
Year: 1996
Language: English
Pages: 476
Chapman & Hall texts in statistical science series
......Page 1
Copyright
......Page 3
Contents
......Page 4
Preface
......Page 12
Preface to the second edition
......Page 16
Preface to the first edition
......Page 18
I. Preparation for analysis
......Page 22
1. What is multivariate analysis?
......Page 24
2. Characterizing data for future analyses
......Page 33
3. Preparing for data analysis
......Page 42
4. Data screening and data transformation
......Page 69
5. Selecting appropriate analyses
......Page 92
II. Applied regression analysis
......Page 104
6. Simple linear regression correlation
......Page 106
7. Multiple regression and correlation
......Page 145
8. Variable selection in regression analysis
......Page 187
9. Special regression topics
......Page 218
III. Multivariate analysis
......Page 246
10. Canonical correlation analysis
......Page 248
11. Discriminant analysis
......Page 264
12. Logistic regression
......Page 302
13. Regression analysis using survival data
......Page 327
14. Principal components analysis
......Page 351
15. Factor analysis
......Page 375
16. Cluster analysis
......Page 402
17. Log-linear analysis
......Page 431
Appendix a: lung function data
......Page 464
Appendix b: lung cancer survival data
......Page 467
Index
......Page 470
