Contingency Tables and Inference for Two-Way Contingency Tables: Probability Structure for Contingency Tables, Comparing Two Proportions, Measuring Association in I J × Tables. Confidence Interval for Association Parameters, Testing Independence in Two-Way Contingency Tables.
Generalized Linear Model: Generalized Linear Model, Generalized Linear Models for Binary Data and Counts, Model Checking.
Logistic Regression-Building and Applying: Interpreting Parameters in Logistic Regression, Inference for Logistic Regression, Logistic Models with Categorical Predictors, Multiple Logistic Regression.
Models for Multinomial Responses: Baseline-Category Logit Models, Cumulative Logit Models, Cumulative Link Models.
Clustered Categorical Data- Marginal and Transitional Models: Marginal Modeling: Maximum Likelihood Approach, Generalized Estimating Equations Approach.