Statistical analytics for health data science with SAS and R / Jeffrey R. Wilson, Ding-Geng Chen, and Karl E. Peace.
| Author/creator | Wilson, Jeffrey |
| Other author | Chen, Ding-Geng. |
| Other author | Peace, Karl E., 1941- |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, Taylor & Francis Group, 2023. |
| Description | 1 online resource |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Series | Chapman & Hall/CRC biostatistics series Chapman & Hall/CRC biostatistics series ^A707265 |
| Contents | Sampling and Data Collection -- Measures of Tendency, Spread, Relative Standing, Association, Belief -- Statistical Modeling of Mean of Continuous and Mean of Binary outcomes -- Modeling of Continuous and Binary Outcomes with Factors: One-way and Two-way ANOVA Models -- Statistical Modeling of Continuous Outcomes with Continuous Explanatory Factors Linear Regression Models -- Statistical Modeling of Continuous Outcomes with Continuous Explanatory Factors Linear Regression Models -- : Statistical Modeling of Binary Outcome with One or More Covariates :Standard Logistic Regression Model -- Generalized Linear Models -- Modeling Repeated Continuous Observations using GEE -- Modeling for Correlated Continuous Responses with Random-Effects -- Modeling Correlated Binary Outcomes through Hierarchical Logistic Regression Models. |
| Abstract | "This book is aimed to compile typical fundamental to advanced statistical methods to be used for health data sciences. This book promotes the applications to health and health-related data. However, the models in this book can be used to analyse any kind of data. The data are analysed 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 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"-- Provided by publisher. |
| General note | "A Chapman & Hall book" |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Source of description | Description based on print version record and CIP data provided by publisher. |
| Issued in other form | Print version: Wilson, Jeffrey (Jeffrey R.). Statistical analytics for health data science with SAS and R First edition. Boca Raton : CRC Press, Taylor & Francis Group, 2023 9781032325620 |
| Genre/form | Electronic books. |
| LCCN | 2022044013 |
| ISBN | 9781003315674 (ebook) |
| ISBN | (hardback) |
| ISBN | (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |