Shein-Chung Chow, Jun Shao, Hansheng Wang

Gebundenes Buch

Sample Size Calculations in Clinical Research

Beschreibung

Praise for the Second Edition:

"... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics

"This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." - Journal of the Royal Statistical Society

Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summaryof current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation.

Features:

Compares the relative merits and disadvantages of statistical methods for sample size calculations

Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages

Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women's health

Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches

This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.

Autor

Shein-Chung Chow, PhD, is a professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine. Dr. Chow is also an adjunct professor at Duke-National University of Singapore Graduate Medical School, an adjunct professor at North Carolina State University, and founding director of the Global Clinical Trial and Research Center in Tianjin, China. He is editor-in-chief of the Journal of Biopharmaceutical Statistics and editor-in-chief of the Chapman & Hall/CRC Biostatistics Series. He is the author or co-author of more than 250 papers and 24 books, including Adaptive Design Methods in Clinical Trials, Second Edition, Handbook of Adaptive Designs in Pharmaceutical and Clinical Development, and Controversial Statistical Issues in Clinical Trials. A fellow of the ASA and member of the ISI, Dr. Chow has received the ASA Chapter Service Recognition Award, the DIA Outstanding Service Award, and the ICSA Extraordinary Achievement Award. Dr. Lokhnygina is an Assistant Professor of Biostatistics and Bioinformatics at Duke University and a faculty member at Duke Clinical Research Institute. Her primary research interests are in statistical methods for multicenter clinical trials, particularly in application to cardiovascular and diabetes research.

Produktdetails

• Chapman & Hall/CRC Biostatistics Series
• Verlag: Chapman and Hall/CRC / Taylor & Francis
• 3. Aufl.
• Seitenzahl: 512
• Erscheinungstermin: 30. August 2017
• Englisch
• Abmessung: 260mm x 183mm x 32mm
• Gewicht: 1132g
• ISBN-13: 9781138740983
• ISBN-10: 1138740985
• Artikelnr.: 49084472

Rezensionen

Praise for the Second Edition:



"... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics

"This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." - Journal of the Royal Statistical

Society

"The book is nicely set out with an introduction to the basic idea of each topic, followed by various formulae that lead to power calculations . . . In all, I consider this book to be well written, and it touches on quite a number of more recent topics in sample size determination. Consequently, it will be a useful addition to clinical statisticians as a point of reference to solve more complex issues in power calculations during the design of a clinical trial." - Steve Su, International Society for Clinical Biostatistics

Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation.

Features:

• Compares the relative merits and disadvantages of statistical methods for sample size calculations



• Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages



• Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women's health



• Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches

This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.