Korosteleva, Olga

Advanced regression models with SAS and R - Boca Raton CRC Press 2019 - xiii, 310 p. Includes illustrations, reference and index

Table of Contents

Introduction : general and generalized linear regression models
Regression models for response with right-skewed distribution
Regression models for binary response
Regression models for categorical response
Regression models for count response
Regression models for over-dispersed count response
Regression models for proportion response
General linear regression models for repeated measures data
Generalized linear regression model for repeated measures data
Hierarchical regression model.

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 an interpretation of estimated regression coefficients and prediction of response for given values of predictors.
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.



R (Computer program language)
SAS (Computer file)
Regression analysis

519.536 / K6A2

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