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Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models.
Modelling Binary Data
Log-Linear Models and Logistic Regression
Regression Models as a Tool in Medical Research
Logistic Regression
Applied Logistic Regression
Regression Models for Categorical, Count, and Related Variables
Methods of Statistical Model Estimation
Statistical Regression Modeling with R
Regression & Linear Modeling
Elementary Regression Modeling
Modeling Count Data
Bayesian Modeling in Bioinformatics