Study guides, Class notes & Summaries

Introduction: Distributions and Inference for Categorical Data Describing Contingency Tables Inference for Contingency Tables Introduction to Generalized Linear Models Logistic Regression Building and Applying Logistic Regression Models Logit Models for Multinomial Responses Loglinear Models for Contingency Tables Building and Extending LoglinearrLogit Models Models for Matched Pairs Analyzing Repeated Categorical Response Data Random Effects: Generalized Linear Mixed Models for Categorical Resp...