Overview
- 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
Part of the book series: ICSA Book Series in Statistics (ICSABSS, volume 9)
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Table of contents (12 chapters)
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Front Matter
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Introduction and Review of Modeling Uncorrelated Observations
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Front Matter
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Analyzing Correlated Data Through Random Component
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Front Matter
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Analyzing Correlated Data Through Systematic Components
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Front Matter
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Analyzing Correlated Data Through the Joint Modeling of Mean and Variance
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Front Matter
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Keywords
About this book
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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Authors and Affiliations
Bibliographic Information
Book Title: Modeling Binary Correlated Responses using SAS, SPSS and R
Authors: Jeffrey R. Wilson, Kent A. Lorenz
Series Title: ICSA Book Series in Statistics
DOI: https://doi.org/10.1007/978-3-319-23805-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2015
Hardcover ISBN: 978-3-319-23804-3Published: 29 October 2015
Softcover ISBN: 978-3-319-37361-4Published: 23 August 2016
eBook ISBN: 978-3-319-23805-0Published: 12 October 2015
Series ISSN: 2199-0980
Series E-ISSN: 2199-0999
Edition Number: 1
Number of Pages: XXIII, 264
Number of Illustrations: 26 b/w illustrations
Topics: Statistical Theory and Methods, Biostatistics, Statistics for Life Sciences, Medicine, Health Sciences