Preface | |

Introduction: Distributions and Inference for Categorical Data | p. 1 |

Categorical Response Data | p. 1 |

Distributions for Categorical Data | |

Statistical Inference for Categorical Data | |

Statistical Inference for Binomial Parameters | |

Statistical Inference for Multinomial Parameters | |

Bayesian Inference for Binomial and Multinomial Parameters Notes Exercises | |

Describing Contingency Tables | |

Probability Structure for Contingency Tables | |

Comparing Two Proportions | |

Conditional Association in Stratified 2x2 Tables | |

Measuring Association in I x J Tables Notes Exercises | |

Inference for Two-Way Contingency Tables | |

Confidence Intervals for Association Parameters | |

Testing Independence in Two-Way Contingency Tables | |

Following-Up Chi-Squared Tests | |

Two-Way Tables with Ordered Classifications | |

Small-Sample Inference for Contingency Tables | |

Bayesian Inference for Two-Way Contingency Tables | |

Extensions for Multiway Tables and Nontabulated Responses Notes Exercises | |

Introduction to Generalized Linear Models | |

The Generalized Linear Model | |

Generalized Linear Models for Binary Data | |

Generalized Linear Models for Counts and Rates | |

Moments and Likelihood for Generalized Linear Models | |

Inference and Model Checking for Generalized Linear Models | |

Fitting Generalized Linear Models | |

Quasi-Likelihood and Generalized Linear Models Notes Exercises | |

Logistic Regression | |

Interpreting Parameters in Logistic Regression | |

Inference for Logistic Regression | |

Logistic Models with Categorical Predictors | |

Multiple Logistic Regression | |

Fitting Logistic Regression Models Notes Exercises | |

Building, Checking, and Applying Logistic Regression Models | |

Strategies in Model Selection | |

Logistic Regression Diagnostics | |

Summarizing the Predictive Power of a Model | |

Mantel-Haenszel and Related Methods for Multiple 2x2 Tables | |

Detecting and Dealing with Infinite Estimates | |

Sample Size and Power Considerations Notes Exercises | |

Alternative Modeling of Binary Response Data | |

Probit and Complementary Log-Log Models | |

Bayesian Inference for Binary Regression | |

Conditional Logistic Regression | |

Smoothing: Kernels, Penalized Likelihood, Generalized Additive Models | |

Issues in Analyzing High-Dimensional Categorical Data Notes Exercises | |

Models for Multinomial Responses | |

Nominal Responses: Baseline-Category Logit Models | |

Ordinal Responses: Cumulative Logit Models | |

Ordinal Responses: Alternative Models | |

Testing Conditional Independence in I ? J ? K Tables | |

Discrete-Choice Models | |

Bayesian Modeling of Multinomial Responses Notes Exercises | |

Loglinear Models for Contingency Tables | |

Loglinear Models for Two-Way Tables | |

Loglinear Models for Independence and Interaction in Three-Way Tables | |

Inference for Loglinear Models | |

Loglinear Models for Higher Dimensions | |

The Loglinear?Logistic Model Connection | |

Loglinear Model Fitting: Likelihood Equations and Asymptotic Distributions | |

Loglinear Model Fitting: Iterative Methods and their Application Notes Exercises | |

Building and Extending Loglinear Models | |

Conditional Independence Graphs and Collapsibility | |

Model Selection and Comparison | |

Residuals for Detecting Cell-Specific Lack of Fit | |

Modeling Ordinal Associations | |

Generalized Loglinear and Association Models, Correlation Models, and Correspondence Analysis | |

Empty Cells and Sparseness in Modeling Contingency Tables | |

Bayesian Loglinear Modeling Notes Exercises | |

Models for Matched Pairs | |

Comparing Dependent Proportions | |

Conditional Logistic Regression for Binary Matched Pairs | |

Marginal Models for Square Contingency Tables | |

Symmetry, Quasi-symmetry, and Quasi-independence | |

Measuring Agreement Between Observers | |

Bradley-Terry Model for Paired Preferences | |

Marginal Models and Quasi-symmetry Models for Matched Sets Notes Exercises | |

Clustered Categorical Data: Marginal and Transitional Models | |

Marginal Modeling: Maximum Likelihood Approach | |

Marginal Modeling: Generalized Estimating Equations Approach | |

Quasi-likelihood and Its GEE Multivariate Extension: Details | |

Transitional Models: Markov Chain and Time Series Models Notes Exercises | |

Clustered Categorical Data: Random Effects Models | |

Random Effects Modeling of Clustered Categorical Data | |

Binary Responses: The Logistic-Normal Model | |

Examples of Random Effects Models for Binary Data | |

Random Effects Models for Multinomial Data | |

Multilevel Models | |

GLMM Fitting, Inference, and Prediction | |

Bayesian Multivariate Categorical Modeling Notes Exercises | |

Other Mixture Models for Discrete Data | |

Latent Class Models | |

Nonparametric Random Effects Models | |

Beta-Binomial Models | |

Negative Binomial Regression | |

Poisson Regression with Random Effects Notes Exercises | |

Non-Model-Based Classification and Clustering | |

Classification: Linear Discriminant Analysis | |

Classification: Tree-Structured Prediction | |

Cluster Analysis for Categorical Data Notes Exercises | |

Large- and Small-Sample Theory for Parametric Models | |

Delta Method | |

Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities | |

Asymptotic Distributions of Residuals and Goodness-of-Fit Statistics | |

Asymptotic Distributions for Logit/Loglinear Models | |

Small-Sample Significance Tests for Contingency Tables | |

Small-Sample Confidence Intervals for Categorical Data | |

Alternative Estimation Theory for Parametric Models Notes Exercises | |

Historical Tour of Categorical Data Analysis | |

Pearson-Yule Association Controversy | |

R. A. Fisher's Contributions | |

Logistic Regression | |

Multiway Contingency Tables and Loglinear Models | |

Bayesian Methods for Categorical Data | |

A Look Forward, and Backward | |

Statistical Software for Categorical Data Analysis | |

Chi-Squared Distribution Values | |

References | |

Author Index | |

Example Index | |

Subject Index | |

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