Categorical Data Analysis Using the SAS System
Categorical Data Analysis Using the SAS System, Second Edition
By: Maura Stokes, Charles S. Davis, and Gary G. Koch
Pages: 648 公卫家园
Statisticians and researchers will find this book a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS. Practical examples from a broad range of applications illustrate the use of the FREQ, LOGISTIC, GENMOD, and CATMOD procedures in a variety of analyses. Other procedures discussed include the PHREG and NPAR1WAY procedures. Topics discussed include assessing association in contingency tables and se ts of tables, logistic regression and conditional logistic regression, weighted least squares modeling, repeated measurements analyses, loglinear models, and bioassay analysis. The second edition has been revised for use with Version 8 of SAS. New topics include additional exact tests, generalized estimating equations, use of the CLASS statement in the LOGISTIC procedure, exact logistic regression using the LOGISTIC procedure, and comparisons of the use of subject-specific models versus population-averaged models.
Maura E. Stokes is Senior Manager of Statistical Applications Research and Development at SAS Institute. She received her DrPH in Biostatistics from the University of North Carolina at Chapel Hill and has taught and written about categorical data analysis for over fifteen years.
Charles S. Davis is Professor of Biostatistics at the University of Iowa. He received his PhD in Biostatistics from the University of Michigan. His research and teaching interests include categorical data analysis and methods for the analysis of repeated measures.
Gary G. Koch is Professor of Biostatistics and Director of the Biometrics Consulting Laboratory at the University of North Carolina at Chapel Hill. He has had a prominent role in the field of categorical data analysis for the last thirty years. He teaches classes and seminars in categorical data analysis, consults in areas of statistical practice, conducts research, and trains many Biostatistics students.
Preface to the Second Edition.
Chapter 1. Introduction.
Chapter 2. The 2 x 2 Table.
Chapter 3. Sets of 2 x 2 Tables.
Chapter 4. Sets of 2 x r and s x 2 Tables.
Chapter 5. The s x r Table.
Chapter 6. Sets of s x r Tables.
Chapter 7. Nonparametric Methods.
Chapter 8. Logistic Regression I: Dichotomous Response.
Chapter 9. Logistic Regression II: Polytomous Response.
Chapter 10. Conditional Logistic Regression.
Chapter 11. Quantal Bioassay Analysis.
Chapter 12. Poisson Regression.
Chapter 13. Weighted Least Squares.
Chapter 14. Modeling Repeated Measurements Data with WLS.
Chapter 15. Generalized Estimating Equations.
Chapter 16. Loglinear Models.
Chapter 17. Categorized Time-to-Event Data.