Modeling Binary Correlated Responses using SAS, SPSS and R (ICSA Book Series in Statistics (9)) Papeback -
by Jeffrey R. Wilson; Kent A. Lorenz
- New
Standard delivery: 9 to 14 days
Details
- Title Modeling Binary Correlated Responses using SAS, SPSS and R (ICSA Book Series in Statistics (9))
- Author Jeffrey R. Wilson; Kent A. Lorenz
- Binding Papeback
- Condition New
- Pages 264
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date pp. 287
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # 6381126225
- ISBN 9783319373614 / 3319373617
- Weight 0.9 lbs (0.41 kg)
- Dimensions 9.21 x 6.14 x 0.61 in (23.39 x 15.60 x 1.55 cm)
- Category Mathematics
- Dewey Decimal Code 519.5
- Quantity available 4
About Cold Books New York, United States
Reader reviews for Modeling Binary Correlated Responses using SAS, SPSS and R (ICSA Book Series in Statistics (9))
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the publisher
From the rear cover
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.