Multiple Testing Problems in Pharmaceutical Statistics PDF Download

Author: Alex Dmitrienko
Publisher: CRC Press
ISBN: 1584889853
Category : Mathematics
Languages : en
Pages : 323

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Book Description
Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple c

Author: Peter H. Westfall
Publisher: John Wiley & Sons
ISBN: 9780471557616
Category : Mathematics
Languages : en
Pages : 382

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Book Description
Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.

Author: Frank Bretz
Publisher: CRC Press
ISBN: 1420010905
Category : Mathematics
Languages : en
Pages : 202

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Book Description
Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org After giving examples of multiplicity problems, the book covers general concepts and basic multiple comparisons procedures, including the Bonferroni method and Simes’ test. It then shows how to perform parametric multiple comparisons in standard linear models and general parametric models. It also introduces the multcomp package in R, which offers a convenient interface to perform multiple comparisons in a general context. Following this theoretical framework, the book explores applications involving the Dunnett test, Tukey’s all pairwise comparisons, and general multiple contrast tests for standard regression models, mixed-effects models, and parametric survival models. The last chapter reviews other multiple comparison procedures, such as resampling-based procedures, methods for group sequential or adaptive designs, and the combination of multiple comparison procedures with modeling techniques. Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. See Dr. Bretz discuss the book.

Author: Douglas G. Altman
Publisher: CRC Press
ISBN: 1000228819
Category : Mathematics
Languages : en
Pages : 624

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Book Description
Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

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: Yosef Hochberg
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 482

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Book Description
Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. With equal emphasis on theory and applications, it establishes the advantages of multiple comparison techniques in reducing error rates and in ensuring the validity of statistical inferences. Provides detailed descriptions of the derivation and implementation of a variety of procedures, paying particular attention to classical approaches and confidence estimation procedures. Also discusses the benefits and drawbacks of other methods. Numerous examples and tables for implementing procedures are included, making this work both practical and informative.

Author: Susan Halabi, PhD
Publisher: Demos Medical Publishing
ISBN: 1935281763
Category : Medical
Languages : en
Pages : 396

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Book Description
Clinical trials are the engine of progress in the development of new drugs and devices for the detection, monitoring, prevention and treatment of cancer. A well conceived, carefully designed and efficiently conducted clinical trial can produce results that change clinical practice overnight, deliver new oncology drugs and diagnostics to the marketplace, and expand the horizon of contemporary thinking about cancer biology. A poorly done trial does little to advance the field or guide clinical practice, consumes precious clinical and financial resources and challenges the validity of the ethical contract between investigators and the volunteers who willingly give their time and effort to benefit future patients. With chapters written by oncologists, researchers, biostatisticians, clinical research administrators, and industry and FDA representatives, Oncology Clinical Trials, provides a comprehensive guide for both early-career and senior oncology investigators into the successful design, conduct and analysis of an oncology clinical trial. Oncology Clinical Trials covers how to formulate a study question, selecting a study population, study design of Phase I, II, and III trials, toxicity monitoring, data analysis and reporting, use of genomics, cost-effectiveness analysis, systemic review and meta-analysis, and many other issues. Many examples of real-life flaws in clinical trials that have been reported in the literature are included throughout. The book discusses clinical trials from start to finish focusing on real-life examples in the development, design and analysis of clinical trials. Oncology Clinical Trials features: A systematic guide to all aspects of the design, conduct, analysis, and reporting of clinical trials in oncology Contributions from oncologists, researchers, biostatisticians, clinical research administrators, and industry and FDA representatives Hot topics in oncology trials including multi-arm trials, meta-analysis and adaptive design, use of genomics, and cost-effectiveness analysis Real-life examples from reported clinical trials included throughout

Author: Alan J. Klockars
Publisher: SAGE
ISBN: 9780803920514
Category : Mathematics
Languages : en
Pages : 92

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Book Description
Describes the most important methods used to investigate differences between levels of an independent variable within an experimental design. Readers will learn not only how to conduct multiple comparisons in experimental designs but also how to better understand and evaluate published research. "A highly readable introduction to multiple comparison methods, which demands little from its reader in the way of background other than some familiarity with analysis of variance." --The Statistician

Author: Sandrine Dudoit
Publisher: Springer
ISBN: 9781441923790
Category : Science
Languages : en
Pages : 0

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Book Description
This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. These are applied to a range of problems in biomedical and genomic research, including identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments; tests of association between gene expression measures and biological annotation metadata; sequence analysis; and genetic mapping of complex traits using single nucleotide polymorphisms. The procedures are based on a test statistics joint null distribution and provide Type I error control in testing problems involving general data generating distributions, null hypotheses, and test statistics.

Author: Gernot Wassmer
Publisher: Springer
ISBN: 3319325620
Category : Medical
Languages : en
Pages : 310

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Book Description
This book provides an up-to-date review of the general principles of and techniques for confirmatory adaptive designs. Confirmatory adaptive designs are a generalization of group sequential designs. With these designs, interim analyses are performed in order to stop the trial prematurely under control of the Type I error rate. In adaptive designs, it is also permissible to perform a data-driven change of relevant aspects of the study design at interim stages. This includes, for example, a sample-size reassessment, a treatment-arm selection or a selection of a pre-specified sub-population. Essentially, this adaptive methodology was introduced in the 1990s. Since then, it has become popular and the object of intense discussion and still represents a rapidly growing field of statistical research. This book describes adaptive design methodology at an elementary level, while also considering designing and planning issues as well as methods for analyzing an adaptively planned trial. This includes estimation methods and methods for the determination of an overall p-value. Part I of the book provides the group sequential methods that are necessary for understanding and applying the adaptive design methodology supplied in Parts II and III of the book. The book contains many examples that illustrate use of the methods for practical application. The book is primarily written for applied statisticians from academia and industry who are interested in confirmatory adaptive designs. It is assumed that readers are familiar with the basic principles of descriptive statistics, parameter estimation and statistical testing. This book will also be suitable for an advanced statistical course for applied statisticians or clinicians with a sound statistical background.