The material covered by this book consists of a collection of regression models beyond linear regression. The linear regression model is presented in the first chapter in order to refresh the reader's memory, emphasize certain points, and set the notation.The subsequent chapters talk about models for categorical data, count data, proportions, longitudinal data, hierarchical data, and others.
The material covered by this book consists of a collection of regression models beyond linear regression. The linear regression model is presented in the first chapter in order to refresh the reader's memory, emphasize certain points, and set the notation.The subsequent chapters talk about models for categorical data, count data, proportions, longitudinal data, hierarchical data, and others.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Olga Korosteleva is an associate professor of statistics in the Department of Mathematics and Statistics at California State University, Long Beach (CSULB). She received a Ph.D. in statistics from Purdue University.
Inhaltsangabe
Multiple Linear Regression Models. Regression Models for Binary Response. Regression Models for Categorical Response. Generalized Linear Models for Count Response. Poisson Regression Model. Generalized Linear Models for Over-dispersed Count Response. Negative Binomial Regression Model. Regression Models for Continuous Proportion Response. Linear Mixed Models for Longitudinal Data. Generalized Linear Mixed Models for Longitudinal Data. Generalized Estimating Equations Regression Model. Hierarchical Regression Models. Structural Equation Modelling.