Categorical Data Analysis Using The SAS® System, 2nd Edition

Table of contents

1. Copyright
2. Preface to the Second Edition
   1. Computing Details
   2. For More Information
3. Acknowledgments
4. Introduction
   1. Overview
   2. Scale of Measurement
   3. Sampling Frameworks
   4. Overview of Analysis Strategies
   5. Working with Tables in the SAS System
   6. Using This Book
5. The 2 × 2 Table
   1. Introduction
   2. Chi-Square Statistics
   3. Exact Tests
   4. Difference in Proportions
   5. Odds Ratio and Relative Risk
   6. Sensitivity and Specificity
   7. McNemar’s Test
6. Sets of 2 × 2 Tables
   1. Introduction
   2. Mantel-Haenszel Test
   3. Measures of Association
7. Sets of 2 × r and s × 2 Tables
   1. Introduction
   2. Sets of 2 × r Tables
   3. Sets of s × 2 Tables
   4. Relationships Between Sets of Tables
8. The s × r Table
   1. Introduction
   2. Association
   3. Exact Tests for Association
   4. Measures of Association
   5. Observer Agreement
   6. Test for Ordered Differences
9. Sets of s × r Tables
   1. Introduction
   2. General Mantel-Haenszel Methodology
   3. Mantel-Haenszel Applications
   4. Advanced Topic: Application to Repeated Measures
10. Nonparametric Methods
    1. Introduction
    2. Wilcoxon-Mann-Whitney Test
    3. Kruskal-Wallis Test
    4. Friedman’s Chi-Square Test
    5. Aligned Ranks Test for Randomized Complete Blocks
    6. Durbin’s Test for Balanced Incomplete Blocks
    7. Rank Analysis of Covariance
11. Logistic Regression I: Dichotomous Response
    1. Introduction
    2. Dichotomous Explanatory Variables
    3. Using the CLASS Statement
    4. Qualitative Explanatory Variables
    5. Continuous and Ordinal Explanatory Variables
    6. A Note on Diagnostics
    7. Maximum Likelihood Estimation Problems and Alternatives
    8. Exact Methods in Logistic Regression
    9. Using the CATMOD and GENMOD Procedures for Logistic Regression
    10. Appendix A: Statistical Methodology for Dichotomous Logistic Regression
12. Logistic Regression II: Polytomous Response
    1. Introduction
    2. Ordinal Response: Proportional Odds Model
    3. Nominal Response: Generalized Logits Model
13. Conditional Logistic Regression
    1. Introduction
    2. Paired Observations from a Highly Stratified Cohort Study
    3. Clinical Trials Study Analysis
    4. Crossover Design Studies
    5. General Conditional Logistic Regression
    6. Paired Observations in a Retrospective Matched Study
    7. 1:m Conditional Logistic Regression
    8. Exact Conditional Logistic Regression in the Stratified Setting
    9. Appendix A: Theory for the Case-Control Retrospective Setting
    10. Appendix B: Theory for Exact Conditional Inference
    11. Appendix C: ODS Macro
14. Quantal Bioassay Analysis
    1. Introduction
    2. Estimating Tolerance Distributions
    3. Comparing Two Drugs
    4. Analysis of Pain Study
15. Poisson Regression
    1. Introduction
    2. Methodology for Poisson Regression
    3. Simple Poisson Counts Example
    4. Poisson Regression for Incidence Densities
    5. Overdispersion in Lower Respiratory Infection Example
16. Weighted Least Squares
    1. Introduction
    2. Weighted Least Squares Methodology
    3. Using PROC CATMOD for Weighted Least Squares Analysis
    4. Analysis of Means: Performing Contrast Tests
    5. Analysis of Proportions: Occupational Data
    6. Obstetrical Pain Data: Advanced Modeling of Means
    7. Analysis of Survey Sample Data
    8. Modeling Rank Measures of Association Statistics
    9. Appendix A: Statistical Methodology for Weighted Least Squares
17. Modeling Repeated Measurements Data with WLS
    1. Introduction
    2. Weighted Least Squares
    3. Advanced Topic: Further Weighted Least Squares Applications
18. Generalized Estimating Equations
    1. Introduction
    2. Methodology
    3. Summary of the GEE Methodology
    4. Passive Smoking Example
    5. Crossover Example
    6. Respiratory Data
    7. Using a Modified Wald Statistic to Assess Model Effects
    8. Diagnostic Data
    9. Using GEE for Count Data
    10. Fitting the Proportional Odds Model
    11. GEE Analyses for Data with Missing Values
    12. Alternating Logistic Regression
    13. Using GEE to Fit a Partial Proportional Odds Model: Univariate Outcome
    14. Using GEE to Account for Overdispersion: Univariate Outcome
    15. Appendix A: Steps to Find the GEE Solution
    16. Appendix B: Macro for Adjusted Wald Statistic
19. Loglinear Models
    1. Introduction
    2. Two-Way Contingency Tables
    3. Three-Way Contingency Tables
    4. Higher-Order Contingency Tables
    5. Correspondence Between Logistic Models and Loglinear Models
    6. Appendix A: Equivalence of the Loglinear and Poisson Regression Models
20. Categorized Time-to-Event Data
    1. Introduction
    2. Life Table Estimation of Survival Rates
    3. Mantel-Cox Test
    4. Piecewise Exponential Models
21. References
22. Wiley Series in Probability and Statistics
23. Wiley Series in Probability and Statistics
24. Books Available from SAS® Press
    1. JMP® Books
25. Index