Advanced Regression Models with SAS and R
Authors: Olga Korosteleva
ISBN-10: 1138049018
ISBN-13: 9781138049017
Edition 版次: 1
Publication Date 出版日期: 2018-12-10
Print Length 页数: 324 pages
5
Book Description
By finelybook
Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression,including models for right-skewed,categorical and hierarchical observations. The book presents the theory as well as fully worked-out numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression,the fitted model is presented along with interpretation of estimated regression coefficients and prediction of response for given values of predictors.
Features:
Presents the theoretical framework for each regression.
Discusses data that are categorical,count,proportions,right-skewed,longitudinal and hierarchical.
Uses examples based on real-life consulting projects.
Provides complete SAS and R codes for each example.
Includes several exercises for every regression.
Advanced Regression Models with SAS and R is designed as a text for an upper division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required.
Contents
Preface
Chapter 1 Introduction: General and Generalized Linear Regression Models
Chapter 2 Regression Models for Response with Right-skewed Distribution
Chapter 3 Regression Models for Binary Response
Chapter 4 Regression Models for Categorical Response
Chapter 5 Regression Models for Count Response
Chapter 6 Regression Models for Overdispersed Count Response
Chapter 7 Regression Models for Proportion Response
Chapter 8 General Linear Regression Models for Repeated Measures Data
Chapter 9 Generalized Linear Regression Models for Repeated Measures Data
Chapter 10 Hierarchical Regression Model
Recommended Books
List of Notation
Subject Index
