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Categorical Data Analysis Using the SAS System (Stokes)

 Author(s)  Maura E. Stokes, Charles S. Davis, Gary G. Koch
 Title  Categorical Data Analysis Using the SAS System
 Edition  2nd Edition
 Year  2000
 Publisher  SAS Institute Inc.; John Wiley & Sons, Inc.
 ISBN  0-471-22424-3


Statisticians and researchers will find Maura Stokes, Charles Davis, and Gary Koch's Categorical Data Analysis Using the SAS System, Second Edition, to be 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 sets of tables, logistic regression and conditional logistic regression, weighted least squares modeling, repeated measurements analyses, log-linear models, and bioassay analysis.

The second edition has been revised for use with SAS 8. 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.

Table of Contents

Chapter 1: Introduction

  • Overview
  • Scale of Measurement
  • Sampling Frameworks
  • Overview of Analysis Strategies
  • Working with Tables in the SAS System
  • Using This Book

Chapter 2: The 2 x 2 Table
  • Introduction
  • Chi-Square Statistics
  • Exact Tests
  • Difference in Proportions
  • Odds Ratio and Relative Risk
  • Sensitivity and Specificity
  • McNemar's Test

Chapter 3: Sets of 2 x 2 Tables

  • Introduction
  • Mantel-Haenszel Test
  • Measures of Association

Chapter 4: Sets of 2 x r and s x 2 Tables

  • Introduction
  • Sets of 2 x r Tables
  • Sets of s x 2 Tables
  • Relationships Between Sets of Tables

Chapter 5: The s x r Tables

  • Introduction
  • Association
  • Exact Tests for Association
  • Measures of Association
  • Observer Agreement
  • Test for Ordered Differences

Chapter 6: Sets of s x r Tables

  • Introduction
  • General Mantel-Haenszel Methodology
  • Mantel-Haenszel Applications
  • Advanced Topic: Application to Repeated Measures

Chapter 7: Nonparametric Methods

  • Introduction
  • Wilcoxon-Mann-Whitney Test
  • Kruskal-Wallis Test
  • Friedman's Chi-Square Test
  • Aligned Ranks Test for Randomized Complete Blocks
  • Durbin's Test for Balanced Incomplete Blocks
  • Rank Analysis of Covariance

Chapter 8: Logistic Regression I: Dichotomous Response

  • Introduction
  • Dichotomous Explanatory Variables
  • Using the CLASS Statement
  • Qualitative Explanatory Variables
  • Continuous and Ordinal Explanatory Variables
  • A Note on Diagnostics
  • Maximum Likelihood Estimation Problems and Alternatives
  • Exact Methods in Logistic Regression
  • Using the CATMOD and GENMOD Procedures for Logistic Regression
  • Appendix A: Statistical Methodology for Dichotomous Logistic Regression

Chapter 9: Logistic Regression II: Polytomous Response

  • Introduction
  • Ordinal Response: Proportional Odds Model
  • Nominal Response: Generalized Logits Model

Chapter 10: Conditional Logistic Regression
  • Introduction
  • Paired Observations from a Highly Stratified Cohort Study
  • Clinical Trials Study Analysis
  • Crossover Design Studies
  • General Conditional Logistic Regression
  • Paired Observations in a Retrospective Matched Study
  • l:m Conditional Logistic Regression
  • Exact Conditional Logistic Regression in the Stratified Setting
  • Appendix A: Theory for the Case-Control Retrospective Setting
  • Appendix B: Theory for Exact Conditional Inference
  • Appendix C: ODS Macros

Chapter 11: Quantal Bioassay Analysis

  • Introduction
  • Estimating Tolerance Distributions
  • Comparing Two Drugs
  • Analysis of Pain Study

Chapter 12: Poisson Regression
  • Introduction
  • Methodology for Poisson Regression
  • Simple Poisson Counts Example
  • Poisson Regression for Incidence Densities
  • Overdispersion in Lower Respiratoy Infection Example

Chapter 13: Weighted Least Squares
  • Introduction
  • Weighted Least Squares Methodology
  • Using PROC CATMOD for Weighted Least Squares Analysis
  • Analysis of Means: Performing Contrast Tests
  • Analysis of Proportions: Occupational Data
  • Obstetrical Pain Data: Advanced Modeling of Means
  • Analysis of Survey Sample Data
  • Modeling Rank Measures of Association Statistics
  • Appendix A: Statistical Methodology for Weighted Least Squares

Chapter 14: Modeling Repeated Measurements Data with WLS
  • Introduction
  • Weighted Least Squares
  • Advanced Topic: Further Weighted Least Square Applications

Chapter 15: Generalized Estimating Equations
  • Introduction
  • Methodology
  • Summary of the GEE Methodology
  • Passive Smoking Example
  • Crossover Example
  • Respiratory Data
  • Using a Modified Wald Statistic to Assess Model Effects
  • Diagnostic Data
  • Using GEE for Count Data
  • Fitting the Proportional Odds Model
  • GEE Analysis for Data with Missing Values
  • Alternating Logistic Regression
  • Using GEE to Fit a Partial Proportional Odds Model: Univariate Outcome
  • Using GEE to Account for Overdispersion: Univariate Outcome
  • Appendix A: Steps to Find the GEE Solution
  • Appendix B: Macros for Adjusted Wald Statistic

Chapter 16: Loglinear Models
  • Introduction
  • Two-Way Contingency Tables
  • Three-Way Contingency Tables
  • Higher-Order Contingency Tables
  • Correspondence Between Logistic Models and Loglinear Models
  • Appendix A: Equivalence of the Loglinear and Poisson Regression Models

Chapter 17: Categorized Time-to-Event Data
  • Introduction
  • Life Table Estimation of Survival Rates
  • Mantel-Cox Test
  • Piecewise Exponential Models



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