Categorical Data Analysis Using the SAS System (2000)
Maura Stokes, Charles S. Davis, Gary G. Koch
Palavras-chave:
Dados técnicos
Editora: SAS Publishing. Número de páginas: 648. Livro em inglês. 2ed, 2000.Comentários
É um livro da editora do SAS, que cobre uma ampla gama de análises de dados categorizados com sua respectiva implementação em SAS. Apesar do enfoque grande no pacote estatístico, a metodologia estatística também tem uma cobertura de destaque.Capítulos
Chapter 1. Introduction1.1 Overview
1.2 Scale of Measurement
1.3 Sampling Frameworks
1.4 Overview of Analysis Strategies
1.5 Working with Tables in the SAS System
1.6 Using This Book
Chapter 2. The 2 x 2 Table
2.1 Introduction
2.2 Chi-Square Statistics
2.3 Exact Tests
2.4 Difference in Proportions
2.5 Odds Ratio and Relative Risk
2.6 Sensitivity and Specificity
2.7 McNemar’s Test
Chapter 3. Sets of 2 x 2 Tables
3.1 Introduction
3.2 Mantel-Haenszel Test
3.3 Measures of Association
Chapter 4. Sets of 2 x r and s x 2 Tables
4.1 Introduction
4.2 Sets of 2 x r Tables
4.3 Sets of s x 2 Tables
4.4 Relationships Between Sets of Tables
Chapter 5. The s x r Table
5.1 Introduction
5.2 Association
5.3 Exact Tests for Association
5.4 Measures of Association
5.5 Observer Agreement
5.6 Test for Ordered Differences
Chapter 6. Sets of s x r Tables
6.1 Introduction
6.2 General Mantel-Haenszel Methodology
6.3 Mantel-Haenszel Applications
6.4 Advanced Topic: Application to Repeated Measures
Chapter 7. Nonparametric Methods
7.1 Introduction
7.2 Wilcoxon-Mann-Whitney Test
7.3 Kruskal-Wallis Test
7.4 Friedman’s Chi-Square Test
7.5 Aligned Ranks Test for Randomized Complete Blocks
7.6 Durbin’s Test for Balanced Incomplete Blocks
7.7 Rank Analysis of Covariance
Chapter 8. Logistic Regression I: Dichotomous Response
8.1 Introduction
8.2 Dichotomous Explanatory Variables
8.3 Using the CLASS Statement
8.4 Qualitative Explanatory Variables
8.5 Continuous and Ordinal Explanatory Variables
8.6 A Note on Diagnostics
8.7 Maximum Likelihood Estimation Problems and Alternatives
8.8 Exact Methods in Logistic Regression
8.9 Using the CATMOD and GENMOD Procedures for Logistic Regression
Appendix A: Statistical Methodology for Dichotomous Logistic Regression
Chapter 9. Logistic Regression II: Polytomous Response
9.1 Introduction
9.2 Ordinal Response: Proportional Odds Model
9.3 Nominal Response: Generalized Logits Model
Chapter 10. Conditional Logistic Regression
10.1 Introduction
10.2 Paired Observations from a Highly Stratified Cohort Study
10.3 Clinical Trials Study Analysis
10.4 Crossover Design Studies
10.5 General Conditional Logistic Regression
10.6 Paired Observations in a Retrospective Matched Study
10.7 1:m Conditional Logistic Regression
10.8 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 Macro
Chapter 11. Quantal Bioassay Analysis
11.1 Introduction
11.2 Estimating Tolerance Distributions
11.3 Comparing Two Drugs
11.4 Analysis of Pain Study
Chapter 12. Poisson Regression
12.1 Introduction
12.2 Methodology for Poisson Regression
12.3 Simple Poisson Counts Example
12.4 Poisson Regression for Incidence Densities
12.5 Overdispersion in Lower Respiratory Infection Example
Chapter 13. Weighted Least Squares
13.1 Introduction
13.2 Weighted Least Squares Methodology
13.3 Using PROC CATMOD for Weighted Least Squares Analysis
13.4 Analysis of Means: Performing Contrast Tests
13.5 Analysis of Proportions: Occupational Data
13.6 Obstetrical Pain Data: Advanced Modeling of Means
13.7 Analysis of Survey Sample Data
13.8 Modeling Rank Measures of Association Statistics
Appendix A: Statistical Methodology for Weighted Least Squares
Chapter 14. Modeling Repeated Measurements Data with WLS
14.1 Introduction
14.2 Weighted Least Squares
14.3 Advanced Topic: Further Weighted Least Squares Applications
Chapter 15. Generalized Estimating Equations
15.1 Introduction
15.2 Methodology
15.3 Summary of the GEE Methodology
15.4 Passive Smoking Example
15.5 Crossover Example
15.6 Respiratory Data
15.7 Using a Modified Wald Statistic to Assess Model Effects
15.8 Diagnostic Data
15.9 Using GEE for Count Data
15.10 Fitting the Proportional Odds Model
15.11 GEE Analyses for Data with Missing Values
15.12 Alternating Logistic Regression
15.13 Using GEE to Fit a Partial Proportional Odds Model: Univariate Outcome
15.14 Using GEE to Account for Overdispersion: Univariate Outcome
Appendix A: Steps to Find the GEE Solution
Appendix B: Macro for Adjusted Wald Statistic
Chapter 16. Loglinear Models
16.1 Introduction
16.2 Two-Way Contingency Tables
16.3 Three-Way Contingency Tables
16.4 Higher-Order Contingency Tables
16.5 Correspondence Between Logistic Models and Loglinear Models
Appendix A: Equivalence of the Loglinear and Poisson Regression Models
Chapter 17. Categorized Time-to-Event Data
17.1 Introduction
17.2 Life Table Estimation of Survival Rates
17.3 Mantel-Cox Test
17.4 Piecewise Exponential Models
