
Statistical Analytics for Health Data Science with SAS and R by Jeffrey Wilson
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. The data and computing programs will be available to facilitate readers' learning experience.-
R for Health Technology Assessment
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Value of Information for Healthcare Decision-Making
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Bayesian Models in Health Technology Assessment
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Statistical Methods for Immunogenicity Assessment
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Randomization, Masking, and Allocation Concealment
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Exposure-Response Modeling
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Mixture Modelling for Medical and Health Sciences
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Data Analysis with Competing Risks and Intermediate States
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Statistics In the Pharmaceutical Industry
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Design and Analysis of Bioavailability and Bioequivalence Studies
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Mixed Effects Models for the Population Approach
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Multiple Testing Problems in Pharmaceutical Statistics
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Machine Learning for Microbiome Statistics
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Master Protocol Clinical Trials for Evidence Generation
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Does This Treatment Cause That Outcome?
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Comparative Effectiveness and Personalized Medicine Research Using Real-World Data
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Age-Period-Cohort Models
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Biostatistics for Bioassay
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Statistical Methods for Survival Trial Design
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Every Coin Has Two Sides
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Group Sequential and Adaptive Methods for Clinical Trials
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Empirical Likelihood Method in Survival Analysis
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Multiregional Clinical Trials for Simultaneous Global New Drug Development
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Adaptive Design Methods in Clinical Trials
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Clinical Trial Data Analysis Using R and SAS
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Bayesian Cost-Effectiveness Analysis of Medical Treatments
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Statistical Methods for Drug Safety
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Emerging Non-Clinical Biostatistics in Biopharmaceutical Development and Manufacturing
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Design & Analysis of Clinical Trials for Economic Evaluation & Reimbursement
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Meta-Analysis in Medicine and Health Policy
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Model-Assisted Bayesian Designs for Dose Finding and Optimization
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Statistical Methods in Drug Combination Studies
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Design and Analysis of Clinical Trials for Predictive Medicine
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Frailty Models in Survival Analysis
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Bayesian Methods in Health Economics
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Survival Analysis in Medicine and Genetics
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Clinical Trial Methodology
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Applied Surrogate Endpoint Evaluation Methods with SAS and R
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Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials
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Design and Analysis of Animal Studies in Pharmaceutical Development
"In summary, Statistical Analytics for Health Data Science with SAS and R excels in demystifying intricate statistical concepts and offers both theoretical grounding and practical experienceWhether you are an applied data scientist, a graduate student, or a public health researcher, this work by Willson, Chen, and Peace is an invaluable asset for learning and applying statistics in real-world settings."
Ali Rahnavard, The George Washingotn University USA, Journal of the American Statistical Association, 2023.
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.
| SKU | Unavailable |
| ISBN 13 | 9781032325620 |
| ISBN 10 | 1032325623 |
| Title | Statistical Analytics for Health Data Science with SAS and R |
| Author | Jeffrey Wilson |
| Series | Chapman And Hall Crc Biostatistics Series |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2023-03-28 |
| Number of pages | 258 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |







































