|
" Advanced regression models with SAS and R / "
Olga Korosteleva.
Document Type
|
:
|
BL
|
Record Number
|
:
|
841162
|
Main Entry
|
:
|
Korosteleva, Olga
|
Title & Author
|
:
|
Advanced regression models with SAS and R /\ Olga Korosteleva.
|
Publication Statement
|
:
|
Boca Raton :: CRC Press, Taylor & Francis Group,, [2019]
|
|
:
|
, ©2019
|
Page. NO
|
:
|
1 online resource :: illustrations
|
ISBN
|
:
|
1315169827
|
|
:
|
: 135169006X
|
|
:
|
: 1351690078
|
|
:
|
: 1351690086
|
|
:
|
: 9781315169828
|
|
:
|
: 9781351690065
|
|
:
|
: 9781351690072
|
|
:
|
: 9781351690089
|
|
:
|
1138049018
|
|
:
|
9781138049017
|
Bibliographies/Indexes
|
:
|
Includes bibliographical references and index.
|
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.
|
Abstract
|
:
|
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 Ris 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. The Author: Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master's students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields.
|
Subject
|
:
|
R (Computer program language)
|
Subject
|
:
|
Regression analysis, Textbooks.
|
Subject
|
:
|
MATHEMATICS-- Applied.
|
Subject
|
:
|
MATHEMATICS-- Probability Statistics-- General.
|
Subject
|
:
|
R (Computer program language)
|
Subject
|
:
|
Regression analysis.
|
Subject
|
:
|
SAS (Computer file)
|
|
:
|
SAS (Computer file)
|
Dewey Classification
|
:
|
519.5/36
|
LC Classification
|
:
|
QA278.2.K6755 2019eb
|
| |