Clinical Trial Data Analysis Using R and SAS by Ding-Geng Chen
This book will provide a thorough presentation of clinical trial methodology with detailed step-by-step illustrations on implementation in software R/SAS. The examples will be based on actual experience of the authors in many areas of clinical drug development. Actual examples of clinical trials will be presented and after understanding the appl-
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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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
". . this book provides a very useful overview of the statistical methods used in the analysis of clinical trials, along with their implementations. This will particularly help clinical practitioners to apply these methodologies in their own scientific problems . . . I would really like to thank the authors, D. Chen, K. E. Peace and P. Zhang, for such a nice readymade reference for clinical trial analysis, with very interesting real data illustrations."
~Abhik Ghosh, International Society for Clinical Biostatistics
Ding-Geng (Din) Chen, Ph.D., is a professor at the University of Rochester Medical Center. Dr. Chen has vast experience in
biostatistical research and clinical trial development and methodology. He has authored or co-authored more than 100 journal
publications on biostatistical methodologies and applications. He is also the co-author (with Dr. Peace) of Clinical Trial Methodology
and Clinical Trial Data Analysis Using R and a co-editor (with Drs. Sun and Peace) of Interval-Censored Time-to-Event Data: Methods
and Applications. He is a member of the American Statistical Association, chair for the STAT section of the American Public Health
Association, an associate editor of the Journal of Statistical Computation and Simulation, and an editorial board member of several
other journals.
Karl E. Peace, Ph.D., is the Georgia Cancer Coalition Distinguished Cancer Scholar, senior research scientist, and professor of
biostatistics in the Jiann-Ping Hsu College of Public Health at Georgia Southern University. He is also an adjunct professor of
biostatistics at the VCU School of Medicine. Dr. Peace is a reviewer or editor of several journals, the founding editor of the Journal of
Biopharmaceutical Statistics, and a fellow of the American Statistical Association. He has authored or co-authored over 150 articles
and 10 books. He has received numerous awards, including the University System of Georgia Board of Regents’ Alumni Hall of Fame
Award, the First President’s Medal for outstanding contributions to Georgia Southern University, and distinguished meritorious service
awards from the American Public Health Association and other organizations. In 2012, the American Statistical Association created the
Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society.
| SKU | Unavailable |
| ISBN 13 | 9780367736217 |
| ISBN 10 | 0367736217 |
| Title | Clinical Trial Data Analysis Using R and SAS |
| Author | Ding-Geng Chen |
| Series | Chapman And Hall Crc Biostatistics Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Routledge |
| Year published | 2020-12-18 |
| Number of pages | 378 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |