دانلود کتاب Categorical Data Analysis

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Preface Contents 1. Introduction 1.1. Categorical Response Data 1.2. Organization of This Book Chapter Notes Problems 2. Describing Two-Way Contingency Tables 2.1. Table Structure for Two Dimensions 2.2. Ways of Comparing Proportions 2.3. Summary Measures of Association 2.4 . Historical Overview Chapter Notes Problems 3. Inference for Two-Way Contingency Tables 3.1. Sampling Distributions 3.2. Testing Goodness-of-Fit 3.3. Testing Independence 3.4. Large-Sample Confidence Intervals 3.5. Exact Tests for Small Samples 3.6. Exact Non-null Inference Chapter Notes Problems 4. Models for Binary Response Variables 4.1. Generalized Linear Models 4.2. Logistic Regression 4.3. Logit Models for Categorical Data 4.4. Using Models to Improve Inferential Power 4.5. Probit and Extreme Value Models 4.6. Model Diagnostics 4.7. Fitting Logit Models 4.8. Conditional Logistic Regression Chapter Notes Problems 5. Loglinear Models 5.1. Loglinear Model for Two Dimensions 5.2. Table Structure for Three Dimensions 5.3. Loglinear Models for Three Dimensions 5.4. Loglinear Models for Higher Dimensions Chapter Notes Problems 6. Fitting Loglinear and Logit Models 6.1. Sufficiency and Likelihood for Loglinear Models 6.2. Estimating Expected Frequencies 6.3. Testing Goodness of Fit 6.4. Estimating Model Parameters 6.5. Iterative Maximum Likelihood Estimation 6.6. Analyzing Rates and Survival Times Using Loglinear Models 6.7. Table Standardization Chapter Notes Problems 7. Building and Applying Loglinear Models 7.1. Partitioning Chi-Squared to Compare Models 7.2. Strategies in Model Selection 7.3. Analysis of Residuals 7.4. Testing Conditional Independence 7.5. Estimating and Comparing Conditional Associations 7.6. Sample Size and Power Considerations 7.7. Empty Cells and Sparseness in Contingency Tables Chapter Notes Problems 8. Loglinear-Logit Models for Ordinal Variables 8.1. Linear-by-Linear Association 8.2. Row Effects and Column Effects Models 8.3. Models for Ordinal Variables in Multidimensional Tables 8.4. Testing Independence for Ordinal Classifications 8.5. Other Models Having Parameter Scores 8.6. Model Selection for Ordinal Variables Chapter Notes Problems 9. Multinomial Response Models 9.1. Generalized Logit Models and Loglinear Models 9.2. Multinomial Logit Models 9.3. Logits for Ordinal Responses 9.4. Cumulative Logit Models 9.5. Cumulative Link Models 9.6. Mean Response Models Chapter Notes Problems 10. Models for Matched Pairs 10.1. Comparing Dependent Proportions 10.2. Symmetry Models 10.3. Marginal Homogeneity 10.4. Square Tables with Ordered Categories 10.5. Measuring Agreement 10.6. Bradley-Terry Model for Paired Comparisons Chapter Notes Problems 11. Analyzing Repeated Categorical Response Data 11.1. Symmetry 11.2. Marginal Homogeneity 11.3. Modeling a Repeated Categorical Response 11.4. Modeling a Repeated Ordinal Response 11.5. Markov Chain Models Chapter Notes Problems 12. Asymptotic Theory for Parametric Models 12.1. Delta Method 12.2. Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities 12.3. Asymptotic Distribution of Residuals and Goodness-of-Fit Statistics 12.4. Asymptotic Distributions for Loglinear Models Chapter Notes Problems 13. Estimation Theory for Parametric Models 13.1. Maximum Likelihood for Generalized Linear Models 13.2. Maximum Likelihood for Loglinear Models 13.3. Weighted Least Squares for Categorical Data 13.4. Bayesian Inference for Categorical Data 13.5. Other Methods of Estimation Chapter Notes Problems Appendix A. Using Computer Software to Analyze Categorical Data A.1. Software Packages A.2. Listings of Computer Routines by Chapter Appendix B. A Twentieth-Century Tour of Categorical Data Analysis Appendix C. Chi-Squared Distribution Values for Various Right-Hand Tail Probabilities Bibliography Index of Examples Index of Selected Notation Author Index Subject Index