Preface | p. xiii |
Introduction: Distributions and Inference for Categorical Data | p. 1 |
Categorical Response Data | p. 1 |
Distributions for Categorical Data | p. 5 |
Statistical Inference for Categorical Data | p. 9 |
Statistical Inference for Binomial Parameters | p. 14 |
Statistical Inference for Multinomial Parameters | p. 21 |
Notes | p. 26 |
Problems | p. 28 |
Describing Contingency Tables | p. 36 |
Probability Structure for Contingency Tables | p. 36 |
Comparing Two Proportions | p. 43 |
Partial Association in Stratified 2 X 2 Tables | p. 47 |
Extensions for I X J Tables | p. 54 |
Notes | p. 59 |
Problems | p. 60 |
Inference for Contingency Tables | p. 70 |
Confidence Intervals for Association Parameters | p. 70 |
Testing Independence in Two-Way Contingency Tables | p. 78 |
Following-Up Chi-Squared Tests | p. 80 |
Two-Way Tables with Ordered Classifications | p. 86 |
Small-Sample Tests of Independence | p. 91 |
Small-Sample Confidence Intervals for 2 x 2 Tables | p. 98 |
Extensions for Multiway Tables and Nontabulated Responses | p. 101 |
Notes | p. 102 |
Problems | p. 104 |
Introduction to Generalized Linear Models | p. 115 |
Generalized Linear Model | p. 116 |
Generalized Linear Models for Binary Data | p. 120 |
Generalized Linear Models for Counts | p. 125 |
Moments and Likelihood for Generalized Linear Models | p. 132 |
Inference for Generalized Linear Models | p. 139 |
Fitting Generalized Linear Models | p. 143 |
Quasi-likelihood and Generalized Linear Models | p. 149 |
Generalized Additive Models | p. 153 |
Notes | p. 155 |
Problems | p. 156 |
Logistic Regression | p. 165 |
Interpreting Parameters in Logistic Regression | p. 166 |
Inference for Logistic Regression | p. 172 |
Logit Models with Categorical Predictors | p. 177 |
Multiple Logistic Regression | p. 182 |
Fitting Logistic Regression Models | p. 192 |
Notes | p. 196 |
Problems | p. 197 |
Building and Applying Logistic Regression Models | p. 211 |
Strategies in Model Selection | p. 211 |
Logistic Regression Diagnostics | p. 219 |
Inference About Conditional Associations in 2 x 2 x K Tables | p. 230 |
Using Models to Improve Inferential Power | p. 236 |
Sample Size and Power Considerations | p. 240 |
Probit and Complementary Log-Log Models | p. 245 |
Conditional Logistic Regression and Exact Distributions | p. 250 |
Notes | p. 257 |
Problems | p. 259 |
Logit Models for Multinomial Responses | p. 267 |
Nominal Responses: Baseline-Category Logit Models | p. 267 |
Ordinal Responses: Cumulative Logit Models | p. 274 |
Ordinal Responses: Cumulative Link Models | p. 282 |
Alternative Models for Ordinal Responses | p. 286 |
Testing Conditional Independence in I x J x K Tables | p. 293 |
Discrete-Choice Multinomial Logit Models | p. 298 |
Notes | p. 302 |
Problems | p. 302 |
Loglinear Models for Contingency Tables | p. 314 |
Loglinear Models for Two-Way Tables | p. 314 |
Loglinear Models for Independence and Interaction in Three-Way Tables | p. 318 |
Inference for Loglinear Models | p. 324 |
Loglinear Models for Higher Dimensions | p. 326 |
The Loglinear-Logit Model Connection | p. 330 |
Loglinear Model Fitting: Likelihood Equations and Asymptotic Distributions | p. 333 |
Loglinear Model Fitting: Iterative Methods and their Application | p. 342 |
Notes | p. 346 |
Problems | p. 347 |
Building and Extending Loglinear/Logit Models | p. 357 |
Association Graphs and Collapsibility | p. 357 |
Model Selection and Comparison | p. 360 |
Diagnostics for Checking Models | p. 366 |
Modeling Ordinal Associations | p. 367 |
Association Models | p. 373 |
Association Models, Correlation Models, and Correspondence Analysis | p. 379 |
Poisson Regression for Rates | p. 385 |
Empty Cells and Sparseness in Modeling Contingency Tables | p. 391 |
Notes | p. 398 |
Problems | p. 400 |
Models for Matched Pairs | p. 409 |
Comparing Dependent Proportions | p. 410 |
Conditional Logistic Regression for Binary Matched Pairs | p. 414 |
Marginal Models for Square Contingency Tables | p. 420 |
Symmetry, Quasi-symmetry, and Quasi-independence | p. 423 |
Measuring Agreement Between Observers | p. 431 |
Bradley-Terry Model for Paired Preferences | p. 436 |
Marginal Models and Quasi-symmetry Models for Matched Sets | p. 439 |
Notes | p. 442 |
Problems | p. 444 |
Analyzing Repeated Categorical Response Data | p. 455 |
Comparing Marginal Distributions: Multiple Responses | p. 456 |
Marginal Modeling: Maximum Likelihood Approach | p. 459 |
Marginal Modeling: Generalized Estimating Equations Approach | p. 466 |
Quasi-likelihood and Its GEE Multivariate Extension: Details | p. 470 |
Markov Chains: Transitional Modeling | p. 476 |
Notes | p. 481 |
Problems | p. 482 |
Random Effects: Generalized Linear Mixed Models for Categorical Responses | p. 491 |
Random Effects Modeling of Clustered Categorical Data | p. 492 |
Binary Responses: Logistic-Normal Model | p. 496 |
Examples of Random Effects Models for Binary Data | p. 502 |
Random Effects Models for Multinomial Data | p. 513 |
Multivariate Random Effects Models for Binary Data | p. 516 |
GLMM Fitting, Inference, and Prediction | p. 520 |
Notes | p. 526 |
Problems | p. 527 |
Other Mixture Models for Categorical Data | p. 538 |
Latent Class Models | p. 538 |
Nonparametric Random Effects Models | p. 545 |
Beta-Binomial Models | p. 553 |
Negative Binomial Regression | p. 559 |
Poisson Regression with Random Effects | p. 563 |
Notes | p. 565 |
Problems | p. 566 |
Asymptotic Theory for Parametric Models | p. 576 |
Delta Method | p. 577 |
Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities | p. 582 |
Asymptotic Distributions of Residuals and Goodness-of-Fit Statistics | p. 587 |
Asymptotic Distributions for Logit/Loglinear Models | p. 592 |
Notes | p. 594 |
Problems | p. 595 |
Alternative Estimation Theory for Parametric Models | p. 600 |
Weighted Least Squares for Categorical Data | p. 600 |
Bayesian Inference for Categorical Data | p. 604 |
Other Methods of Estimation | p. 611 |
Notes | p. 615 |
Problems | p. 616 |
Historical Tour of Categorical Data Analysis | p. 619 |
Pearson-Yule Association Controversy | p. 619 |
R. A. Fisher's Contributions | p. 622 |
Logistic Regression | p. 624 |
Multiway Contingency Tables and Loglinear Models | p. 625 |
Recent (and Future?) Developments | p. 629 |
Using Computer Software to Analyze Categorical Data | p. 632 |
Software for Categorical Data Analysis | p. 632 |
Examples of SAS Code by Chapter | p. 634 |
Chi-Squared Distribution Values | p. 654 |
References | p. 655 |
Examples Index | p. 689 |
Author Index | p. 693 |
Subject Index | p. 701 |
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