Statistical Analytics for Health Data Science with SAS and R

This book aims to compile typical fundamental-to-advanced statistical methods to be used for health
data sciences. Although the book promotes applications to health and health-related data, the
models in the book can be used to analyze any kind of data. The data are analyzed with the commonly
used statistical software of R/SAS (with online supplementary on SPSS/Stata). The data and
computing programs will be available to facilitate readers' learning experience. There has been
considerable attention to making statistical methods and analytics available to health data science
researchers and students. This book brings it all together to provide a concise point-of-reference
for the most commonly used statistical methods from the fundamental level to the advanced level. We
envisage this book will contribute to the rapid development in health data science. We provide
straightforward explanations of the collected statistical theory and models, compilations of a
variety of publicly available data, and illustrations of data analytics using commonly used
statistical software of SAS/R. We will have the data and computer programs available for readers to
replicate and implement the new methods. The primary readers would be applied data scientists and
practitioners in any field of data science, applied statistical analysts and scientists in public
health, academic researchers, and graduate students in statistics and biostatistics. The secondary
readers would be R&D professionals/practitioners in industry and governmental agencies. This
book can be used for both teaching and applied research.

本書旨在彙編典型的從基礎到高級的統計方法，以應用於健康數據科學。儘管本書主要針對健康和與健康相關的數據進行應用，但其中的模型可用於分析任何類型的數據。本書使用常用的統計軟件R/SAS（並提供SPSS/Stata的在線補充資料）來分析數據。為了方便讀者學習，本書提供數據和計算程序。近年來，將統計方法和分析技術提供給健康數據科學研究人員和學生已經受到了相當的關注。本書將這些內容整合在一起，為從基礎到高級水平上最常用的統計方法提供了簡潔的參考。我們希望本書能夠促進健康數據科學的快速發展。本書對收集的統計理論和模型進行了清晰的解釋，彙編了各種公開可用的數據，並使用SAS/R等常用統計軟件進行了數據分析的示例。我們將提供數據和計算程序供讀者複製和實施新方法。主要讀者包括應用數據科學家和從事任何數據科學領域的從業人員、應用統計分析師和公共衛生科學家、學術研究人員以及統計學和生物統計學的研究生。次要讀者包括工業和政府機構的研發專業人員/從業人員。本書可用於教學和應用研究。

Jeffrey Wilson, Ph.D. Professor in Biostatistics and Associate Dean of Research Department of Economics W. P. Carey School of Business, Arizona State University, USA.

Ding-Geng Chen, Ph.D. Professor and Executive Director in Biostatistics College of Health Solutions Arizona State University, USA.

Dr. Karl E. Peace is the Georgia Cancer Coalition Distinguished Cancer Scholar (GCCDCS), Senior Research Scientist and Professor of Biostatistics in the Jiann-Ping Hsu College of Public Health (JPHCOPH) at Georgia Southern University (GSU). He was responsible for establishing the Jiann-Ping Hsu College of Public Health - the first college of public health in the University System of GA (USG). He is the architect of the MPH in Biostatistics - the first-degree program in Biostatistics in the USG and Founding Director of the Karl E. Peace Center for Biostatistics in the JPHCOPH. Dr. Peace holds the Ph.D. in Biostatistics from the Medical College of Virginia, the M.S. in Mathematics from Clemson University, the B.S. in Chemistry from Georgia Southern College, and a Health Science Certificate from Vanderbilt University.

Jeffrey Wilson, Ph.D. 是亞利桑那州立大學W. P. Carey商學院經濟學系的生物統計學教授和研究副院長。

Ding-Geng Chen, Ph.D. 是亞利桑那州立大學健康解決方案學院生物統計學系的教授和執行主任。

Karl E. Peace 博士是喬治亞南方大學Jiann-Ping Hsu公共衛生學院生物統計學的喬治亞癌症聯盟傑出癌症學者(GCCDCS)，高級研究科學家和教授。他負責建立了喬治亞南方大學Jiann-Ping Hsu公共衛生學院 - 喬治亞大學系統中第一所公共衛生學院。他是生物統計學碩士學位計劃的設計者 - 喬治亞大學系統中第一個生物統計學學位計劃，並且是JPHCOPH的Karl E. Peace生物統計學中心的創始主任。Peace博士擁有維吉尼亞醫學院的生物統計學博士學位，克萊姆森大學的數學碩士學位，喬治亞南方大學的化學學士學位，以及范德堡大學的健康科學證書。