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| Preface | |
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| Introduction: Distributions and Inference for Categorical Data | |
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| Categorical Response Data | |
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| Distributions for Categorical Data | |
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| Statistical Inference for Categorical Data | |
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| Statistical Inference for Binomial Parameters | |
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| Statistical Inference for Multinomial Parameters | |
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| Notes | |
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| Problems | |
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| Describing Contingency Tables | |
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| Probability Structure for Contingency Tables | |
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| Comparing Two Proportions | |
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| Partial Association in Stratified 2 X 2 Tables | |
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| Extensions for I X J Tables | |
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| Notes | |
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| Problems | |
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| Inference for Contingency Tables | |
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| Confidence Intervals for Association Parameters | |
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| Testing Independence in Two-Way Contingency Tables | |
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| Following-Up Chi-Squared Tests | |
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| Two-Way Tables with Ordered Classifications | |
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| Small-Sample Tests of Independence | |
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| Small-Sample Confidence Intervals for 2 x 2 Tables | |
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| Extensions for Multiway Tables and Nontabulated Responses | |
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| Notes | |
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| Problems | |
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| Introduction to Generalized Linear Models | |
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| Generalized Linear Model | |
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| Generalized Linear Models for Binary Data | |
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| Generalized Linear Models for Counts | |
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| Moments and Likelihood for Generalized Linear Models | |
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| Inference for Generalized Linear Models | |
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| Fitting Generalized Linear Models | |
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| Quasi-likelihood and Generalized Linear Models | |
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| Generalized Additive Models | |
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| Notes | |
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| Problems | |
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| Logistic Regression | |
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| Interpreting Parameters in Logistic Regression | |
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| Inference for Logistic Regression | |
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| Logit Models with Categorical Predictors | |
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| Multiple Logistic Regression | |
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| Fitting Logistic Regression Models | |
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| Notes | |
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| Problems | |
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| Building and Applying Logistic Regression Models | |
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| Strategies in Model Selection | |
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| Logistic Regression Diagnostics | |
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| Inference About Conditional Associations in 2 x 2 x K Tables | |
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| Using Models to Improve Inferential Power | |
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| Sample Size and Power Considerations | |
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| Probit and Complementary Log-Log Models | |
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| Conditional Logistic Regression and Exact Distributions | |
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| Notes | |
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| Problems | |
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| Logit Models for Multinomial Responses | |
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| Nominal Responses: Baseline-Category Logit Models | |
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| Ordinal Responses: Cumulative Logit Models | |
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| Ordinal Responses: Cumulative Link Models | |
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| Alternative Models for Ordinal Responses | |
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| Testing Conditional Independence in I x J x K Tables | |
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| Discrete-Choice Multinomial Logit Models | |
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| Notes | |
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| Problems | |
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| Loglinear Models for Contingency Tables | |
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| Loglinear Models for Two-Way Tables | |
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| Loglinear Models for Independence and Interaction in Three-Way Tables | |
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| Inference for Loglinear Models | |
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| Loglinear Models for Higher Dimensions | |
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| The Loglinear-Logit Model Connection | |
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| Loglinear Model Fitting: Likelihood Equations and Asymptotic Distributions | |
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| Loglinear Model Fitting: Iterative Methods and their Application | |
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| Notes | |
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| Problems | |
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| Building and Extending Loglinear/Logit Models | |
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| Association Graphs and Collapsibility | |
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| Model Selection and Comparison | |
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| Diagnostics for Checking Models | |
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| Modeling Ordinal Associations | |
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| Association Models | |
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| Association Models, Correlation Models, and Correspondence Analysis | |
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| Poisson Regression for Rates | |
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| Empty Cells and Sparseness in Modeling Contingency Tables | |
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| Notes | |
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| Problems | |
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| Models for Matched Pairs | |
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| Comparing Dependent Proportions | |
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| Conditional Logistic Regression for Binary Matched Pairs | |
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| Marginal Models for Square Contingency Tables | |
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| Symmetry, Quasi-symmetry, and Quasi-independence | |
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| Measuring Agreement Between Observers | |
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| Bradley-Terry Model for Paired Preferences | |
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| Marginal Models and Quasi-symmetry Models for Matched Sets | |
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| Notes | |
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| Problems | |
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| Analyzing Repeated Categorical Response Data | |
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| Comparing Marginal Distributions: Multiple Responses | |
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| Marginal Modeling: Maximum Likelihood Approach | |
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| Marginal Modeling: Generalized Estimating Equations Approach | |
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| Quasi-likelihood and Its GEE Multivariate Extension: Details | |
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| Markov Chains: Transitional Modeling | |
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| Notes | |
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| Problems | |
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| Random Effects: Generalized Linear Mixed Models for Categorical Responses | |
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| Random Effects Modeling of Clustered Categorical Data | |
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| Binary Responses: Logistic-Normal Model | |
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| Examples of Random Effects Models for Binary Data | |
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| Random Effects Models for Multinomial Data | |
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| Multivariate Random Effects Models for Binary Data | |
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| GLMM Fitting, Inference, and Prediction | |
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| Notes | |
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| Problems | |
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| Other Mixture Models for Categorical Data | |
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| Latent Class Models | |
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| Nonparametric Random Effects Models | |
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| Beta-Binomial Models | |
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| Negative Binomial Regression | |
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| Poisson Regression with Random Effects | |
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| Notes | |
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| Problems | |
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| Asymptotic Theory for Parametric Models | |
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| Delta Method | |
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| Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities | |
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| Asymptotic Distributions of Residuals and Goodness-of-Fit Statistics | |
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| Asymptotic Distributions for Logit/Loglinear Models | |
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| Notes | |
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| Problems | |
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| Alternative Estimation Theory for Parametric Models | |
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| Weighted Least Squares for Categorical Data | |
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| Bayesian Inference for Categorical Data | |
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| Other Methods of Estimation | |
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| Notes | |
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| Problems | |
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| Historical Tour of Categorical Data Analysis | |
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| Pearson-Yule Association Controversy | |
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| R. A. Fisher's Contributions | |
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| Logistic Regression | |
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| Multiway Contingency Tables and Loglinear Models | |
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| Recent (and Future?) Developments | |
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| Using Computer Software to Analyze Categorical Data | |
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| Software for Categorical Data Analysis | |
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| Examples of SAS Code by Chapter | |
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| Chi-Squared Distribution Values | |
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| References | |
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| Examples Index | |
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| Author Index | |
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| Subject Index | |