Overview
- Features the significant contributions of many leading statisticians and data scientists to contemporary health sciences
- Includes a comprehensive review of statistical methods and new approaches in health research to guide the reader in learning efficiently
- Covers new developments in EHR data analysis, clinical trials, FDR, big network analytics, applications in GWAS, graphical modeling in genomic studies, survival analysis, and functional data analysis
- Offers innovative statistical procedures, computer program, new data sets, and novel applications in modern health research
Part of the book series: Emerging Topics in Statistics and Biostatistics (ETSB)
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Table of contents (21 chapters)
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Front Matter
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Health Data Analysis and Applications to EHR Data
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Front Matter
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Clinical Trials, FDR, and Applications in Health Science
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Front Matter
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Big Data Analytics and Its Applications
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Front Matter
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Survival Analysis and Functional Data Analysis
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Front Matter
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Keywords
- fluorence image data
- clinical trial
- survival analysis
- gene expression analysis
- surveillance streams
- electronic health records
- clustering methods
- flase discovery rate
- Alzheimer's disease
- classification
- support vector machine
- functional data analysis
- genome-wide association studies
- classifier
- biological network
- infectious disease epidemiology
About this book
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include:
Health data analysis and applications to EHR data
Clinical trials, FDR, and applications in health science
Big network analytics and its applications in GWAS
Survival analysis and functional data analysis
Graphical modelling in genomic studies
The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
Editors and Affiliations
About the editors
Professor Yichuan Zhao is a professor of statistics at Georgia State University in Atlanta. He has a joint appointment as associate member of the Neuroscience Institute, and he is also an affiliated faculty member of the School of Public Health at Georgia State University. His current research interest focuses on survival analysis, empirical likelihood methods, nonparametric statistics, analysis of ROC curves, bioinformatics, Monte Carlo methods, and statistical modelling of fuzzy systems. He has published 100 research articles in statistics and biostatistics, has co-edited four books on statistics, biostatistics and data science, and has been invited to deliver more than 200 research talks nationally and internationally. Dr. Zhao has organized the Workshop Series on Biostatistics and Bioinformatics since its initiation in 2012. He also organized the 25th ICSA Applied Statistics Symposium in Atlanta as a chair of the organizing committee to great success. He is currently serving as associate editor, or on the editorial board, for several statistical journals. Dr. Zhao is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and serves on the Board of Directors, ICSA.
Professor (Din) Ding-Geng Chen is a fellow of the American Statistical Association. He is an honorary professor at the School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, South Africa and an extraordinary professor at the Department of Statistics, University of Pretoria, South Africa. Professor Chen has written more than 200 refereed publications and co-authored/co-edited 33 books on clinical trial methodology, meta-analysis, causal inference and public health statistics. This work is partially supported by the National Research Foundation of South Africa (Grant Number 127727) and the South African National Research Foundation (NRF) and South African Medical Research Council(SAMRC) (South African DST-NRF-SAMRC SARChI Research Chair in Biostatistics, Grant Number 114613).
Bibliographic Information
Book Title: Modern Statistical Methods for Health Research
Editors: Yichuan Zhao, (Din) Ding-Geng Chen
Series Title: Emerging Topics in Statistics and Biostatistics
DOI: https://doi.org/10.1007/978-3-030-72437-5
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 2021
Hardcover ISBN: 978-3-030-72436-8Published: 15 October 2021
Softcover ISBN: 978-3-030-72439-9Published: 15 October 2022
eBook ISBN: 978-3-030-72437-5Published: 14 October 2021
Series ISSN: 2524-7735
Series E-ISSN: 2524-7743
Edition Number: 1
Number of Pages: XXV, 496
Number of Illustrations: 82 b/w illustrations
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Biomedicine, general