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Author: Jay Bartroff
Publisher: Springer Science & Business Media
ISBN: 1461461146
Category : Medical
Languages : en
Pages : 250
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Book Description
Sequential Experimentation in Clinical Trials: Design and Analysis is developed from decades of work in research groups, statistical pedagogy, and workshop participation. Different parts of the book can be used for short courses on clinical trials, translational medical research, and sequential experimentation. The authors have successfully used the book to teach innovative clinical trial designs and statistical methods for Statistics Ph.D. students at Stanford University. There are additional online supplements for the book that include chapter-specific exercises and information. Sequential Experimentation in Clinical Trials: Design and Analysis covers the much broader subject of sequential experimentation that includes group sequential and adaptive designs of Phase II and III clinical trials, which have attracted much attention in the past three decades. In particular, the broad scope of design and analysis problems in sequential experimentation clearly requires a wide range of statistical methods and models from nonlinear regression analysis, experimental design, dynamic programming, survival analysis, resampling, and likelihood and Bayesian inference. The background material in these building blocks is summarized in Chapter 2 and Chapter 3 and certain sections in Chapter 6 and Chapter 7. Besides group sequential tests and adaptive designs, the book also introduces sequential change-point detection methods in Chapter 5 in connection with pharmacovigilance and public health surveillance. Together with dynamic programming and approximate dynamic programming in Chapter 3, the book therefore covers all basic topics for a graduate course in sequential analysis designs.
Author: Jay Bartroff
Publisher: Springer Science & Business Media
ISBN: 1461461146
Category : Medical
Languages : en
Pages : 250
Get Book Here
Book Description
Sequential Experimentation in Clinical Trials: Design and Analysis is developed from decades of work in research groups, statistical pedagogy, and workshop participation. Different parts of the book can be used for short courses on clinical trials, translational medical research, and sequential experimentation. The authors have successfully used the book to teach innovative clinical trial designs and statistical methods for Statistics Ph.D. students at Stanford University. There are additional online supplements for the book that include chapter-specific exercises and information. Sequential Experimentation in Clinical Trials: Design and Analysis covers the much broader subject of sequential experimentation that includes group sequential and adaptive designs of Phase II and III clinical trials, which have attracted much attention in the past three decades. In particular, the broad scope of design and analysis problems in sequential experimentation clearly requires a wide range of statistical methods and models from nonlinear regression analysis, experimental design, dynamic programming, survival analysis, resampling, and likelihood and Bayesian inference. The background material in these building blocks is summarized in Chapter 2 and Chapter 3 and certain sections in Chapter 6 and Chapter 7. Besides group sequential tests and adaptive designs, the book also introduces sequential change-point detection methods in Chapter 5 in connection with pharmacovigilance and public health surveillance. Together with dynamic programming and approximate dynamic programming in Chapter 3, the book therefore covers all basic topics for a graduate course in sequential analysis designs.
Author: John Whitehead
Publisher: John Wiley & Sons
ISBN: 9780471975502
Category : Science
Languages : en
Pages : 342
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Book Description
This book details all aspects of sequential clinical trials from preliminary planning, through the monitoring of the trial, to the final analysis of the results. Emphasis is placed on the triangular test and other procedures based on straight line stopping boundaries. These methods allow for frequent or occasional interim analyses and permit the analysis of a wide variety of patient responses. Alternative procedures are also covered in detail, and these include -spending function methods, repeated confidence intervals and Bayesian approaches to sequential clinical trials.
Author: P. Armitage
Publisher: John Wiley & Sons
ISBN:
Category : Medical
Languages : en
Pages : 216
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Book Description
Author: Toshimitsu Hamasaki
Publisher: Springer
ISBN: 4431559000
Category : Mathematics
Languages : en
Pages : 118
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Book Description
This book focuses on group sequential methods for clinical trials with co-primary endpoints based on the decision-making frameworks for: (1) rejecting the null hypothesis (stopping for efficacy), (2) rejecting the alternative hypothesis (stopping for futility), and (3) rejecting the null or alternative hypothesis (stopping for either futility or efficacy), where the trial is designed to evaluate whether the intervention is superior to the control on all endpoints. For assessing futility, there are two fundamental approaches, i.e., the decision to stop for futility based on the conditional probability of rejecting the null hypothesis, and the other based on stopping boundaries using group sequential methods. In this book, the latter approach is discussed. The book also briefly deals with the group sequential methods for clinical trials designed to evaluate whether the intervention is superior to the control on at least one endpoint. In addition, the book describes sample size recalculation and the resulting effect on power and type I error rate. The book also describes group sequential strategies for three-arm clinical trials to demonstrate the non-inferiority of experimental intervention to actively control and to assess the assay sensitivity to placebo control.
Author: Christopher Jennison
Publisher: CRC Press
ISBN: 9781584888581
Category : Mathematics
Languages : en
Pages : 416
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Book Description
Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion. Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models. Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool.
Author: Haipeng Xing
Publisher: Intl Food Policy Res Inst
ISBN:
Category : Social Science
Languages : en
Pages : 28
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Book Description
Inspired by the wide adoption of rigorous randomized controlled trials (RCTs) in medical research, economists and other social scientists have increasingly used RCTs in their research. As researchers pick up projects amenable to the RCT methodology, they likely leave out important questions to which RCTs cannot be directly applied. As a result, RCTs have been criticized for the proclivity of addressing trivial questions. As a matter of fact, in medical research RCTs are an integral part of adaptive sequential experiment design—a few steps must be taken to screen out drugs that have toxins and strong side effects before running any RCTs on humans. In this paper, we argue that economists can learn a great deal from the design principles implemented in medical research. We develop a theoretical model to show the logic of adaptive sequential experiment design in the presence of uncertainty over negative effects and discuss how to choose samples in a population to minimize the experiment cost. We also point out the applications of our proposed framework in the economic domain, such as economic reforms and new product design.
Author: David Harrington
Publisher: Springer Science & Business Media
ISBN: 1461401402
Category : Medical
Languages : en
Pages : 213
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Book Description
This book will examine current issues and controversies in the design of clinical trials, including topics in adaptive and sequential designs, the design of correlative genomic studies, the design of studies in which missing data is anticipated. Each chapter will be written by an expert conducting research in the topic of that chapter. As a collection, the chapters would be intended to serve as a guidance for statisticians designing trials.
Author: Joseph L. Fleiss
Publisher: John Wiley & Sons
ISBN: 1118031172
Category : Mathematics
Languages : en
Pages : 458
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Book Description
First published in 1986, this unique reference to clinical experimentation remains just as relevant today. Focusing on the principles of design and analysis of studies on human subjects, this book utilizes and integrates both modern and classical designs. Coverage is limited to experimental comparisons of treatments, or in other words, clinical studies in which treatments are assigned to subjects at random.
Author: Tian Zhao
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 188
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Book Description
With the rapid growth of the pharmaceutical industry, it became particularly important to develop efficient statistical techniques for conducting clinical trials. Practically clinical trials nowadays are conducted to answer many questions rather than exploring just one hypothesis. A treatment has to pass the efficacy and safety standards minimally. Handling multiplicity in clinical trials has become a hot topic. During the last two decades, a number of new statistical techniques appeared that improved the overall power of multiple testing procedures while still controlling the familywise Type I error rate. However, a large portion of modern clinical trials is conducted sequentially. The last five years or so, Bartroff and Lai, De and Baron, applied stepwise testing of multiple hypotheses. The procedures were open-ended. But the standard practice requires any clinical trials to be completed by the given date. Any stopping rules have to be truncated. This is the main difference in the problem considered in this dissertation from all the previously proposed methods. In this dissertation, we derived the simultaneous testing of multiple hypotheses that: - control the familywise Type I and Type II error rates; - terminate sampling with probability one at or before the given number of sampled groups; - optimize the expected sample size. For the purpose of testing multiple hypotheses, with a given truncation point, we developed a new group sequential procedure based on the truncated sequential probability ratio test. Our method resulted in an improved single-hypothesis testing that appeared to be more efficient than Pollock's method proposed earlier for the same problem. Extending this to multiple hypotheses by means of Holm-Bonferroni stepwise approach, we derive a truncated group sequential procedure for the simultaneous testing of multiple hypotheses that controls familywise Type I and Type II errors in the strong sense. The new methods can be applied to any truncated sequential sampling for multiple comparisons. Optimizing the expected sampling cost of a clinical trial in this context inevitably implies reduction in the cost of medical treatments, and therefore, it ultimately results in the reduced cost of health care.
Author: Murray R. Selwyn
Publisher: CRC Press
ISBN: 9780849394614
Category : Science
Languages : en
Pages : 176
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Book Description
Let this down-to-earth book be your guide to the statistical integrity of your work. Without relying on the detailed and complex mathematical explanations found in many other statistical texts, Principles of Experimental Design for the Life Sciences teaches how to design, conduct, and interpret top-notch life science studies. Learn about the planning of biomedical studies, the principles of statistical design, sample size estimation, common designs in biological experiments, sequential clinical trials, high dimensional designs and process optimization, and the correspondence between objectives, design, and analysis. Each of these important topics is presented in an understandable and non-technical manner, free of statistical jargon and formulas. Written by a biostatistical consultant with 25 years of experience, Principles of Experimental Design for the Life Sciences is filled with real-life examples from the author's work that you can quickly and easily apply to your own. These examples illustrate the main concepts of experimental design and cover a broad range of application areas in both clinical and nonclinical research. With this one innovative, helpful book you can improve your understanding of statistics, enhance your confidence in your results, and, at long last, shake off those statistical shackles!
