Overview
- Covers statistical methods and their applications to public health research in a multi-disciplinary approach by experts in the field
- Compiles the data & related software in innovative statistical methods so readers can use the software for their own data analysis
- Shares important implications for model development and data analysis
- Can serve as reference for public health and biomedical research and as a text for use in courses on causal inference at the graduate level
Part of the book series: ICSA Book Series in Statistics (ICSABSS)
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Table of contents (15 chapters)
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Modelling Clustered Data
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Modelling Incomplete or Missing Data
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Healthcare Research Models
Keywords
About this book
Reviews
“The book is a compilation of new developments in statistical methods and applications relevant in public health research. … The primary audience is statisticians and researchers in biomedical and public health research. … Each chapter ends with a set of references for further reading. … This is an excellent book, with chapters addressing innovative statistical methods for specific statistical situations, targeted at researchers in the biomedical or public health fields.” (Kamesh Sivagnanam, Doody’s Book Reviews, January, 2016)
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Innovative Statistical Methods for Public Health Data
Editors: Ding-Geng (Din) Chen, Jeffrey Wilson
Series Title: ICSA Book Series in Statistics
DOI: https://doi.org/10.1007/978-3-319-18536-1
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: 978-3-319-18535-4Published: 12 September 2015
Softcover ISBN: 978-3-319-36641-8Published: 22 October 2016
eBook ISBN: 978-3-319-18536-1Published: 31 August 2015
Series ISSN: 2199-0980
Series E-ISSN: 2199-0999
Edition Number: 1
Number of Pages: XIV, 351
Number of Illustrations: 23 b/w illustrations, 22 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Public Health, Laboratory Medicine