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Sample Size Determination And Power

Author: Thomas P. Ryan
Publisher: John Wiley & Sons
ISBN: 1118439228
Size: 42.53 MB
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A comprehensive approach to sample size determination and power with applications for a variety of fields Sample Size Determination and Power features a modern introduction to the applicability of sample size determination and provides a variety of discussions on broad topics including epidemiology, microarrays, survival analysis and reliability, design of experiments, regression, and confidence intervals. The book distinctively merges applications from numerous fields such as statistics, biostatistics, the health sciences, and engineering in order to provide a complete introduction to the general statistical use of sample size determination. Advanced topics including multivariate analysis, clinical trials, and quality improvement are addressed, and in addition, the book provides considerable guidance on available software for sample size determination. Written by a well-known author who has extensively class-tested the material, Sample Size Determination and Power: Highlights the applicability of sample size determination and provides extensive literature coverage Presents a modern, general approach to relevant software to guide sample size determination including CATD (computer-aided trial design) Addresses the use of sample size determination in grant proposals and provides up-to-date references for grant investigators An appealing reference book for scientific researchers in a variety of fields, such as statistics, biostatistics, the health sciences, mathematics, ecology, and geology, who use sampling and estimation methods in their work, Sample Size Determination and Power is also an ideal supplementary text for upper-level undergraduate and graduate-level courses in statistical sampling.

Sample Size Calculations

Author: Paul Mathews
Publisher: Mathews Malnar and Bailey
ISBN: 0615324614
Size: 15.36 MB
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Sample Size Calculations: Practical Methods for Engineers and Scientists presents power and sample size calculations for common statistical analyses including methods for means, standard deviations, proportions, counts, regression, correlation, and measures of agreement. Topics of special interest to quality engineering professionals include designed experiments, reliability studies, statistical process control, acceptance sampling, process capability analysis, statistical tolerancing, and gage error studies. The book emphasizes approximate methods, but exact methods are presented when the approximate methods fail. Monte Carlo and bootstrap methods are introduced for situations that don't satisfy the assumptions of the analytical methods. Solutions are presented for more than 170 example problems and solutions for selected example problems using PASS, MINITAB, Piface, and R are posted on the Internet.

Epidemiological Research Methods

Author: Don McNeil
Publisher: John Wiley & Sons
ISBN: 9780471961963
Size: 16.91 MB
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The concepts of epidemiology, the science that uses statistical methods to investigate associations between risk factors and disease outcomes in human populations, are developed using examples involving real data from published studies. The relevant statistical methods are developed systematically to provide an integrated approach to observational and experimental studies. After covering basic measurement, study design, and study credibility issues, the author continues with basic statistical methods and techniques for adjusting risk estimates for confounders. Statistical models including logistic regression and the proportional hazards model for survival analysis are explained in detail in the following chapters, concluding with an explanation of the general methods for determining the sample size and power requirements for an epidemiological study. Taking advantage of the power, accessibility and user-friendliness of modern computer packages, the author uses a variety of interesting data sets and graphical displays to illustrate the methods. Epidemiological Research Methods will be of interest to students and research workers who need to learn and appreciate modern approaches to the subject. Without unnecessary emphasis on mathematics or theory, the book will enable the reader to gain a greater level of understanding of the underlying methods than is normally provided in books on epidemiology.

Sample Size Calculations In Clinical Research

Author: Shein-Chung Chow
Publisher: CRC Press
ISBN: 0824748239
Size: 34.40 MB
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Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical research and development, Sample Size Calculation in Clinical Research explores the causes of discrepancies and how to avoid them. This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions. The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.

Sample Sizes For Clinical Trials

Author: Steven A. Julious
Publisher: CRC Press
ISBN: 9781584887409
Size: 50.59 MB
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Drawing on various real-world applications, Sample Sizes for Clinical Trials takes readers through the process of calculating sample sizes for many types of clinical trials. It provides descriptions of the calculations with a practical emphasis. Focusing on normal, binary, ordinal, and survival data, the book explores a range of trials, including superiority, equivalence, non-inferiority, bioequivalence, and precision for both parallel group and crossover designs. The author discusses how trial objectives impact the study design with respect to the derivation of formulae for sample size calculations. He uses real-life studies throughout to show how the concepts and calculations can be employed. This work underscores the importance of sample size calculation in the design of a clinical trial. With useful calculation tables throughout, it enables readers to quickly find an appropriate formula, formula application, and associated worked example. Watch the author speak about this book at JSM 2012 in San Diego.

Statistical Methods For Rates And Proportions

Author: Joseph L. Fleiss
Publisher: John Wiley & Sons
ISBN:
Size: 51.52 MB
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Includes a new chapter on logistic regression. Discusses the design and analysis of random trials. Explores the latest applications of sample size tables. Contains a new section on binomial distribution.

Applications Of Statistics To Industrial Experimentation

Author: Cuthbert Daniel
Publisher: John Wiley & Sons
ISBN: 0470317175
Size: 64.69 MB
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Other volumes in the Wiley Series in Probability and Mathematical Statistics, Ralph A. Bradley, J. Stuart Hunter, David G. Kendall, & Geoffrey S. Watson, Advisory Editors Statistical Models in Applied Science Karl V. Bury Of direct interest to engineers and applied scientists, this book presents general principles of statistics and specific distribution methods and models. Prominent distribution properties and methods that are useful over a wide range of applications are covered in detail. The strengths and weaknesses of the distributional models are fully described, giving the reader a firm, intuitive approach to the selection of the model most appropriate to the problem at hand. 1975 656 pp. Fitting Equations To Data Computer Analysis of Multifactor Data for Scientists and Engineers Cuthbert Daniel & Fred S. Wood With the assistance of John W. Gorman The purpose of this book is to help the serious data analyst, scientist, or engineer with a computer to: recognize the strengths and limitations of his data; test the assumptions implicit in the least squares methods used to fit the data; select appropriate forms of the variables; judge which combinations of variables are most influential; and state the conditions under which the fitted equations are applicable. Throughout, mathematics is kept at the level of college algebra. 1971 342 pp. Methods for Statistical Analysis of Reliability And Life Data Nancy R. Mann, Ray E. Schafer & Nozer D. Singpurwalla This book introduces failure models commonly used in reliability analysis, and presents the most useful methods for analyzing the life data of these models. Highlights include: material on accelerated life testing; a comprehensive treatment of estimation and hypothesis testing; a critical survey of methods for system-reliability confidence bonds; and methods for simulation of life data and for testing fit. 1974 564 pp.

Statistical Intervals

Author: William Q. Meeker
Publisher: John Wiley & Sons
ISBN: 1118594959
Size: 20.41 MB
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Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: • Likelihood-based statistical intervals • Nonparametric bootstrap intervals • Parametric bootstrap and other simulation-based intervals • An introduction to Bayesian intervals • Bayesian intervals for the popular binomial, Poisson and normal distributions • Statistical intervals for Bayesian hierarchical models • Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals. William Q. Meeker is Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He is co-author of Statistical Methods for Reliability Data (Wiley, 1998) and of numerous publications in the engineering and statistical literature and has won many awards for his research. Gerald J. Hahn served for 46 years as applied statistician and manager of an 18-person statistics group supporting General Electric and has co-authored four books. His accomplishments have been recognized by GE’s prestigious Coolidge Fellowship and 19 professional society awards. Luis A. Escobar is Professor of Statistics at Louisiana State University. He is co-author of Statistical Methods for Reliability Data (Wiley, 1998) and several book chapters. His publications have appeared in the engineering and statistical literature and he has won several research and teaching awards.

Clinical Trials

Author: Steven Piantadosi
Publisher: John Wiley & Sons
ISBN: 1118959213
Size: 13.74 MB
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Presents elements of clinical trial methods that are essential in planning, designing, conducting, analyzing, and interpreting clinical trials with the goal of improving the evidence derived from these important studies This Third Edition builds on the text’s reputation as a straightforward, detailed, and authoritative presentation of quantitative methods for clinical trials. Readers will encounter the principles of design for various types of clinical trials, and are then skillfully guided through the complete process of planning the experiment, assembling a study cohort, assessing data, and reporting results. Throughout the process, the author alerts readers to problems that may arise during the course of the trial and provides common sense solutions. All stages of therapeutic development are discussed in detail, and the methods are not restricted to a single clinical application area. The authors bases current revisions and updates on his own experience, classroom instruction, and feedback from teachers and medical and statistical professionals involved in clinical trials. The Third Edition greatly expands its coverage, ranging from statistical principles to new and provocative topics, including alternative medicine and ethics, middle development, comparative studies, and adaptive designs. At the same time, it offers more pragmatic advice for issues such as selecting outcomes, sample size, analysis, reporting, and handling allegations of misconduct. Readers familiar with the First and Second Editions will discover revamped exercise sets; an updated and extensive reference section; new material on endpoints and the developmental pipeline, among others; and revisions of numerous sections. In addition, this book: • Features accessible and broad coverage of statistical design methods—the crucial building blocks of clinical trials and medical research -- now complete with new chapters on overall development, middle development, comparative studies, and adaptive designs • Teaches readers to design clinical trials that produce valid qualitative results backed by rigorous statistical methods • Contains an introduction and summary in each chapter to reinforce key points • Includes discussion questions to stimulate critical thinking and help readers understand how they can apply their newfound knowledge • Provides extensive references to direct readers to the most recent literature, and there are numerous new or revised exercises throughout the book Clinical Trials: A Methodologic Perspective, Third Edition is a textbook accessible to advanced undergraduate students in the quantitative sciences, graduate students in public health and the life sciences, physicians training in clinical research methods, and biostatisticians and epidemiologists. Steven Piantadosi, MD, PhD, is the Phase One Foundation Distinguished Chair and Director of the Samuel Oschin Cancer Institute, and Professor of Medicine at Cedars-Sinai Medical Center in Los Angeles, California. Dr. Piantadosi is one of the world’s leading experts in the design and analysis of clinical trials for cancer research. He has taught clinical trials methods extensively in formal courses and short venues. He has advised numerous academic programs and collaborations nationally regarding clinical trial design and conduct, and has served on external advisory boards for the National Institutes of Health and other prominent cancer programs and centers. The author of more than 260 peer-reviewed scientific articles, Dr. Piantadosi has published extensively on research results, clinical applications, and trial methodology. While his papers have contributed to many areas of oncology, he has also collaborated on diverse studies outside oncology including lung disease and degenerative neurological disease.