Modern Bayesian Statistics In Clinical Research
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Modern Bayesian Statistics In Clinical Research
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Author : Ton J. Cleophas
language : en
Publisher: Springer
Release Date : 2018-07-31
Modern Bayesian Statistics In Clinical Research written by Ton J. Cleophas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Medical categories.
The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions. Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results? Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them. SPSS statistical software version 25 (2017) has started to provide a combined module entitled Bayesian Statistics including almost all of the modern Bayesian tests (Bayesian t-tests, analysis of variance (anova), linear regression, crosstabs etc.). Modern Bayesian statistics is based on biological likelihoods, and may better fit clinical data than traditional tests based normal distributions do. This is the first edition to systematically imply modern Bayesian statistics in traditional clinical data analysis. This edition also demonstrates that Markov Chain Monte Carlo procedures laid out as Bayesian tests provide more robust correlation coefficients than traditional tests do. It also shows that traditional path statistics are both textually and conceptionally like Bayes theorems, and that structural equations models computed from them are the basis of multistep regressions, as used with causal Bayesian networks.
Elementary Bayesian Biostatistics
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Author : Lemuel A. Moye
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Elementary Bayesian Biostatistics written by Lemuel A. Moye and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
Bayesian analyses have made important inroads in modern clinical research due, in part, to the incorporation of the traditional tools of noninformative priors as well as the modern innovations of adaptive randomization and predictive power. Presenting an introductory perspective to modern Bayesian procedures, Elementary Bayesian Biostatistics explo
Bayesian Precision Medicine
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Author : Peter F. Thall
language : en
Publisher: CRC Press
Release Date : 2024-05-07
Bayesian Precision Medicine written by Peter F. Thall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-07 with Mathematics categories.
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer. Features: Describes the connection between causal analysis and statistical inference Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applications Presents adaptive methods for clustering similar patient subgroups to improve efficiency Describes Bayesian nonparametric regression analyses of real-world datasets from oncology Provides pointers to software for implementation Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.
Modern Approaches To Clinical Trials Using Sas Classical Adaptive And Bayesian Methods
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Author : Sandeep Menon
language : en
Publisher: SAS Institute
Release Date : 2015-12-09
Modern Approaches To Clinical Trials Using Sas Classical Adaptive And Bayesian Methods written by Sandeep Menon and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-09 with Computers categories.
This book covers domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods applicable to and used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, it covers topics including: dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs incorporating historical data; adaptive sample size re-estimation and randomization to allocate subjects to effective treatments; population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology and rheumatology. --
Bayesian Thinking In Biostatistics
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Author : Gary L Rosner
language : en
Publisher: CRC Press
Release Date : 2021-03-16
Bayesian Thinking In Biostatistics written by Gary L Rosner and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-16 with Mathematics categories.
Praise for Bayesian Thinking in Biostatistics: "This thoroughly modern Bayesian book ...is a 'must have' as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of illuminating applications. These are activated by excellent coverage of computing methods and provision of code. Their content on model assessment, robustness, data-analytic approaches and predictive assessments...are essential to valid practice. The numerous exercises and professional advice make the book ideal as a text for an intermediate-level course..." -Thomas Louis, Johns Hopkins University "The book introduces all the important topics that one would usually cover in a beginning graduate level class on Bayesian biostatistics. The careful introduction of the Bayesian viewpoint and the mechanics of implementing Bayesian inference in the early chapters makes it a complete self- contained introduction to Bayesian inference for biomedical problems....Another great feature for using this book as a textbook is the inclusion of extensive problem sets, going well beyond construed and simple problems. Many exercises consider real data and studies, providing very useful examples in addition to serving as problems." - Peter Mueller, University of Texas With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently use, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests. Key Features Applies a Bayesian perspective to applications in biomedical science Highlights advances in clinical trial design Goes beyond standard statistical models in the book by introducing Bayesian nonparametric methods and illustrating their uses in data analysis Emphasizes estimation of biomedically relevant quantities and assessment of the uncertainty in this estimation Provides programs in the BUGS language, with variants for JAGS and Stan, that one can use or adapt for one's own research The intended audience includes graduate students in biostatistics, epidemiology, and biomedical researchers, in general Authors Gary L. Rosner is the Eli Kennerly Marshall, Jr., Professor of Oncology at the Johns Hopkins School of Medicine and Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Purushottam (Prakash) W. Laud is Professor in the Division of Biostatistics, and Director of the Biostatistics Shared Resource for the Cancer Center, at the Medical College of Wisconsin. Wesley O. Johnson is professor Emeritus in the Department of Statistics as the University of California, Irvine.
Bayesian Methods In Pharmaceutical Research
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Author : Emmanuel Lesaffre
language : en
Publisher: CRC Press
Release Date : 2020-04-15
Bayesian Methods In Pharmaceutical Research written by Emmanuel Lesaffre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-15 with Medical categories.
Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.
Bayesian Approaches To Clinical Trials And Health Care Evaluation
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Author : David J. Spiegelhalter
language : en
Publisher: John Wiley & Sons
Release Date : 2004-05-05
Bayesian Approaches To Clinical Trials And Health Care Evaluation written by David J. Spiegelhalter and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-05-05 with Mathematics categories.
READ ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council’s biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries. Order a copy of this author’s comprehensive text TODAY! The Bayesian approach involves synthesising data and judgement in order to reach conclusions about unknown quantities and make predictions. Bayesian methods have become increasingly popular in recent years, notably in medical research, and although there are a number of books on Bayesian analysis, few cover clinical trials and biostatistical applications in any detail. Bayesian Approaches to Clinical Trials and Health-Care Evaluation provides a valuable overview of this rapidly evolving field, including basic Bayesian ideas, prior distributions, clinical trials, observational studies, evidence synthesis and cost-effectiveness analysis. Covers a broad array of essential topics, building from the basics to more advanced techniques. Illustrated throughout by detailed case studies and worked examples Includes exercises in all chapters Accessible to anyone with a basic knowledge of statistics Authors are at the forefront of research into Bayesian methods in medical research Accompanied by a Web site featuring data sets and worked examples using Excel and WinBUGS - the most widely used Bayesian modelling package Bayesian Approaches to Clinical Trials and Health-Care Evaluation is suitable for students and researchers in medical statistics, statisticians in the pharmaceutical industry, and anyone involved in conducting clinical trials and assessment of health-care technology.
Bayesian Designs For Phase I Ii Clinical Trials
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Author : Taylor & Francis Group
language : en
Publisher: CRC Press
Release Date : 2021-12-13
Bayesian Designs For Phase I Ii Clinical Trials written by Taylor & Francis Group and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-13 with categories.
This book is the first to focus on Bayesian phase I-II clinical trials. It describes many problems with the conventional phase I-phase II paradigm and covers a large number of modern Bayesian phase I-II clinical trial designs.
Bayesian Adaptive Methods For Clinical Trials
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Author : Scott M. Berry
language : en
Publisher: CRC Press
Release Date : 2010-07-19
Bayesian Adaptive Methods For Clinical Trials written by Scott M. Berry and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-19 with Mathematics categories.
Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer's disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adapti
Innovative Strategies Statistical Solutions And Simulations For Modern Clinical Trials
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Author : Mark Chang
language : en
Publisher: CRC Press
Release Date : 2019-03-20
Innovative Strategies Statistical Solutions And Simulations For Modern Clinical Trials written by Mark Chang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-20 with Mathematics categories.
"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.