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Icsa Book Series in Statistics Ser.: Modeling Binary Correlated Responses Using SAS, SPSS and R by Jeffrey Wilson and Kent A. Lorenz (2015, Hardcover)
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MODELING BINARY CORRELATED RESPONSES USING SAS, SPSS AND R (ICSA BOOK SERIES IN STATISTICS) By Jeffrey R. Wilson & Kent A. Lorenz - Hardcover.
- Buy it nowMODELING BINARY CORRELATED RESPONSES USING SAS, SPSS AND R By Jeffrey R. Wilson
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About this product
Product Identifiers
PublisherSpringer International Publishing A&G
ISBN-103319238043
ISBN-139783319238043
eBay Product ID (ePID)215908264
Product Key Features
Number of PagesXxiii, 264 Pages
LanguageEnglish
Publication NameModeling Binary Correlated Responses Using Sas, SPSS and R
SubjectBiostatistics, Probability & Statistics / General, Statistics
Publication Year2015
TypeTextbook
AuthorJeffrey Wilson, Kent A. Lorenz
Subject AreaMathematics, Social Science, Medical
SeriesIcsa Book Series in Statistics Ser.
FormatHardcover
Dimensions
Item Weight214.6 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Reviews"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)
Dewey Edition23
Series Volume Number9
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal300.15195
Table Of ContentIntroduction 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.
SynopsisIntroduction 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., 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.
LC Classification NumberQA276-280
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