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Modeling Binary Correlated Responses using SAS, SPSS and R: ICSA Book Series in Statistics, cartea 9

Autor Jeffrey R. Wilson, Kent A. Lorenz
en Limba Engleză Paperback – 23 aug 2016
Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects.  Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.
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Specificații

ISBN-13: 9783319373614
ISBN-10: 3319373617
Pagini: 264
Ilustrații: XXIII, 264 p. 26 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.41 kg
Ediția:Softcover reprint of the original 1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seria ICSA Book Series in Statistics

Locul publicării:Cham, Switzerland

Cuprins

Introduction to Binary logistic Regression.- Growth of the Logistic Regression Model.- Standard Binary Logistic Regression Model.- Overdispersed Logistic Regression Model.- Weighted Logistic Regression Model.- Generalized Estimating Equations Logistic Regression.- Generalized Method of Moments logistic regression Model.- Exact Logistic Regression Model.- Two-Level Nested Logistic Regression Model.- Hierarchical Logistic Regression models.- Fixed Effects Logistic Regression Model.- Heteroscedastic Logistic Regression Model.

Recenzii

“The monograph is devoted to logistic regression modeling and its extensions useful for complex survey sampling data. … this book will be useful for students and practitioners in various fields needed binary outcome modeling for analysis and predictions in applied research.” (Stan Lipovetsky, Technometrics, Vol. 58 (4), April, 2016)  

Textul de pe ultima copertă

Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects.  Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.

Caracteristici

Timely compilation of methods for correlated binary data analysis that could be otherwise lost to practitioners in the disparate existing literature Data and computer programs are available for readers to replicate model development and data analysis presented in each chapter Chapters progress from an introduction to the analysis of binary data to the realm of correlated binary data Includes supplementary material: sn.pub/extras