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Author : Gordon K. Mak
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (364 download)
Download or read book Bayesian Decision-theoretic Clinical Trial Design Using Gibbs' Sampling written by Gordon K. Mak and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Scott M. Berry
Publisher : CRC Press
ISBN 13 : 1439825513
Total Pages : 316 pages
Book Rating : 4.4/5 (398 download)
Download or read book Bayesian Adaptive Methods for Clinical Trials written by Scott M. Berry and published by CRC Press. This book was released on 2010-07-19 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Ying Yuan
Publisher : CRC Press
ISBN 13 : 1315354225
Total Pages : 238 pages
Book Rating : 4.3/5 (153 download)
Download or read book Bayesian Designs for Phase I-II Clinical Trials written by Ying Yuan and published by CRC Press. This book was released on 2017-12-19 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources. Bayesian Designs for Phase I–II Clinical Trials describes how phase I–II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory clinical trials. It illustrates many of the severe drawbacks with conventional methods used for early-phase clinical trials and presents numerous Bayesian designs for human clinical trials of new experimental treatment regimes. Written by research leaders from the University of Texas MD Anderson Cancer Center, this book shows how Bayesian designs for early-phase clinical trials can explore, refine, and optimize new experimental treatments. It emphasizes the importance of basing decisions on both efficacy and toxicity.
Author : Ming-Hui Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1441969446
Total Pages : 631 pages
Book Rating : 4.4/5 (419 download)
Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer Science & Business Media. This book was released on 2010-07-24 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.
Author : Ari Moshe Lipsky
Publisher :
ISBN 13 :
Total Pages : 470 pages
Book Rating : 4.:/5 ( download)
Download or read book Bayesian Decision-theoretic Trial Design written by Ari Moshe Lipsky and published by . This book was released on 2009 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Emmanuel Lesaffre
Publisher : CRC Press
ISBN 13 : 1351718673
Total Pages : 547 pages
Book Rating : 4.3/5 (517 download)
Download or read book Bayesian Methods in Pharmaceutical Research written by Emmanuel Lesaffre and published by CRC Press. This book was released on 2020-04-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : David J. Spiegelhalter
Publisher : John Wiley & Sons
ISBN 13 : 0470092599
Total Pages : 406 pages
Book Rating : 4.4/5 (7 download)
Download or read book Bayesian Approaches to Clinical Trials and Health-Care Evaluation written by David J. Spiegelhalter and published by John Wiley & Sons. This book was released on 2004-05-05 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Mani Lakshminarayanan
Publisher : CRC Press
ISBN 13 : 1351584162
Total Pages : 453 pages
Book Rating : 4.3/5 (515 download)
Download or read book Bayesian Applications in Pharmaceutical Development written by Mani Lakshminarayanan and published by CRC Press. This book was released on 2019-11-07 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.
Author : Dwaine Stephen Banton
Publisher :
ISBN 13 :
Total Pages : 113 pages
Book Rating : 4.:/5 (128 download)
Download or read book A BAYESIAN DECISION THEORETIC APPROACH TO FIXED SAMPLE SIZE DETERMINATION AND BLINDED SAMPLE SIZE RE-ESTIMATION FOR HYPOTHESIS TESTING written by Dwaine Stephen Banton and published by . This book was released on 2016 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers two related problems that has application in the field of experimental design for clinical trials: • fixed sample size determination for parallel arm, double-blind survival data analysis to test the hypothesis of no difference in survival functions, and • blinded sample size re-estimation for the same. For the first problem of fixed sample size determination, a method is developed generally for testing of hypothesis, then applied particularly to survival analysis; for the second problem of blinded sample size re-estimation, a method is developed specifically for survival analysis. In both problems, the exponential survival model is assumed. The approach we propose for sample size determination is Bayesian decision theoretical, using explicitly a loss function and a prior distribution. The loss function used is the intrinsic discrepancy loss function introduced by Bernardo and Rueda (2002), and further expounded upon in Bernardo (2011). We use a conjugate prior, and investigate the sensitivity of the calculated sample sizes to specification of the hyper-parameters. For the second problem of blinded sample size re-estimation, we use prior predictive distributions to facilitate calculation of the interim test statistic in a blinded manner while controlling the Type I error. The determination of the test statistic in a blinded manner continues to be nettling problem for researchers. The first problem is typical of traditional experimental designs, while the second problem extends into the realm of adaptive designs. To the best of our knowledge, the approaches we suggest for both problems have never been done hitherto, and extend the current research on both topics. The advantages of our approach, as far as we see it, are unity and coherence of statistical procedures, systematic and methodical incorporation of prior knowledge, and ease of calculation and interpretation.
Author : Christian P. Robert
Publisher : Springer Science & Business Media
ISBN 13 : 1475743149
Total Pages : 444 pages
Book Rating : 4.4/5 (757 download)
Download or read book The Bayesian Choice written by Christian P. Robert and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate-level textbook covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics, such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modelling, Monte Carlo integration, and Gibbs sampling. In translating the book from the original French, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.
Author : Guosheng Yin
Publisher : John Wiley & Sons
ISBN 13 : 1118183320
Total Pages : 368 pages
Book Rating : 4.1/5 (181 download)
Download or read book Clinical Trial Design written by Guosheng Yin and published by John Wiley & Sons. This book was released on 2013-06-07 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methods There has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics. Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include: Risk and benefit analysis for toxicity and efficacy trade-offs Bayesian predictive probability trial monitoring Bayesian adaptive randomization Late onset toxicity and response Dose finding in drug combination trials Targeted therapy designs The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials. Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
Author : Say Beng Tan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (595 download)
Download or read book Bayesian Decision Theoretic Methods for Clinical Trials written by Say Beng Tan and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Joseph B. Kadane
Publisher : John Wiley & Sons
ISBN 13 : 1118150597
Total Pages : 344 pages
Book Rating : 4.1/5 (181 download)
Download or read book Bayesian Methods and Ethics in a Clinical Trial Design written by Joseph B. Kadane and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to conduct clinical trials in an ethical and scientificallyresponsible manner This book presents a methodology for clinical trials that producesimproved health outcomes for patients while obtaining sound andunambiguous scientific data. It centers around a real-world testcase--involving a treatment for hypertension after open heartsurgery--and explains how to use Bayesian methods to accommodateboth ethical and scientific imperatives. The book grew out of the direct involvement in the project by adiverse group of experts in medicine, statistics, philosophy, andthe law. Not only do they contribute essays on the scientific,technological, legal, and ethical aspects of clinical trials, butthey also critique and debate each other's opinions, creating aninteresting, personalized text. Bayesian Methods and Ethics in a Clinical Trial Design * Answers commonly raised questions about Bayesian methods * Describes the advantages and disadvantages of this methodcompared with other methods * Applies current ethical theory to a particular class of designfor clinical trials * Discusses issues of informed consent and how to serve a patient'sbest interest while still obtaining uncontaminated scientific data * Shows how to use Bayesian probabilistic methods to createcomputer models from elicited prior opinions of medical experts onthe best treatment for a type of patient * Contains several chapters on the process, results, andcomputational aspects of the test case in question * Explores American law and the legal ramifications of using humansubjects For statisticians and biostatisticians, and for anyone involvedwith medicine and public health, this book provides both apractical guide and a unique perspective on the connection betweentechnological developments, human factors, and some of the largerethical issues of our times.
Author : Ming-Hui Chen
Publisher : Springer
ISBN 13 : 9781441969453
Total Pages : 631 pages
Book Rating : 4.9/5 (694 download)
Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer. This book was released on 2010-08-05 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.
Author : Yiyi Chen
Publisher :
ISBN 13 :
Total Pages : 244 pages
Book Rating : 4.:/5 (298 download)
Download or read book Optimal Adaptive Group Sequential Design for Phase II Clinical Trials written by Yiyi Chen and published by . This book was released on 2008 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Constantine Gatsonis
Publisher : Springer Science & Business Media
ISBN 13 : 1461300355
Total Pages : 441 pages
Book Rating : 4.4/5 (613 download)
Download or read book Case Studies in Bayesian Statistics written by Constantine Gatsonis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24-25, 1999. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the three invited case studies with the accompanying discussion as well as ten contributed pa pers selected by a refereeing process. The majority of case studies in the volume come from biomedical research. However, the reader will also find studies in education and public policy, environmental pollution, agricul ture, and robotics. INVITED PAPERS The three invited cases studies at the workshop discuss problems in ed ucational policy, clinical trials design, and environmental epidemiology, respectively. 1. In School Choice in NY City: A Bayesian Analysis ofan Imperfect Randomized Experiment J. Barnard, C. Frangakis, J. Hill, and D. Rubin report on the analysis of the data from a randomized study conducted to evaluate the New YorkSchool Choice Scholarship Pro gram. The focus ofthe paper is on Bayesian methods for addressing the analytic challenges posed by extensive non-compliance among study participants and substantial levels of missing data. 2. In Adaptive Bayesian Designs for Dose-Ranging Drug Trials D. Berry, P. Mueller, A. Grieve, M. Smith, T. Parke, R. Blazek, N.
Author : Ruitao Lin
Publisher :
ISBN 13 : 9781361043813
Total Pages : pages
Book Rating : 4.0/5 (438 download)
Download or read book Bayesian Adaptive Methods for Phase I Clinical Trials written by Ruitao Lin and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Bayesian Adaptive Methods for Phase I Clinical Trials" by Ruitao, Lin, 林瑞涛, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The primary objective of phase I dose-finding trials is to determine the maximum tolerated dose (MTD), which is typically defined as the dose with the dose-limiting toxicity probability closest to the target toxicity probability. The American Society of Clinical Oncology (ASCO) recently published an update of the ASCO policy statement to call for new phase I trial designs to allow for more efficient escalation to the therapeutic dose levels in order to cope with the changing landscape in cancer research. In this thesis, innovative and robust designs for single- or multiple-agent phase I dose-finding trials are studied. To enhance robustness and efficiency, two nonparametric methods are proposed to locate the MTD in single-agent phase I clinical trials without imposing any parametric assumption on the underlying distribution of the toxicity curve. First, a uniformly most powerful Bayesian interval (UMPBI) design is developed for dose finding, where the optimal interval is determined by the rejection region of the uniformly most powerful Bayesian test. UMPBI is easy to implement and can be nicely interpreted. Compared with existing interval designs, the proposed UMPBI design exhibits a unique feature of convergence to the MTD. Next, a nonparametric overdose control (NOC) method is proposed by casting dose finding in a Bayesian model selection framework. Each dose assignment under NOC is determined such that the posterior probability of overdosing is controlled. In addition, NOC is incorporated with a fractional imputation method to deal with late-onset toxicity outcomes. Both of the UMPBI and NOC designs are flexible, as well as possessing sound theoretical support and desirable numerical performance. In the era of precision medicine, combination therapy is playing an increasingly important role in drug development. However, drug combinations often lead to a high-dimensional dose searching space compared to conventional single-agent dose finding, especially when three or more drugs are combined for treatment. Most of the current dose-finding designs aim to quantify the toxicity probability space using certain prespecified yet complicated models. Not only do these models characterize each individual drug's toxicity profile, but they also need to quantify their interaction effects, which often leads to multi-parameter models. In order to stabilize the current practice of dose finding in drug-combination trials with limited sample sizes, a random walk Bayesian optimal interval (RW-BOIN) design and a Bootstrap aggregating continual reassessment method (Bagging CRM) are proposed. RW-BOIN is built on the basis of the single-agent BOIN design, and it can be utilized to tackle high-dimensional dose-finding problems. A convergence theorem is established to ensure the validity of RW-BOIN. On the other hand, Bagging CRM implements a dimension reduction technique and some ensemble methods in machine learning, so that the toxicity probability space can be stably reduced to a one-dimensional searching line. Simulation studies show that both RW-BOIN and Bagging CRM have comparative and robust operating characteristics compared with existing approaches under various dose-toxicity scenarios. All of the proposed methods are exemplified with real phase I dose-finding trials. Subjects: Bayesian statistical decision theory Clinical trials - Statistical methods
