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Adaptive design methods in clinical trials / Shein-Chung Chow ; Mark Chang
Boca Raton, FL : CRC Press, 2012.
xvi, 39, 2.6-17.4 p. : Illustration ; 24 cm.
Ký hiệu phân loại (DDC): 610.724
With new statistical and scientific issues arising in adaptive clinical trial design, including the U.S. FDA's recent draft guidance, a new edition of one of the first books on the topic is needed. Adaptive Design Methods in Clinical Trials, Second Edition reflects recent developments and regulatory positions on the use of adaptive designs in clinical trials. It unifies the vast and continuously growing literature and research activities on regulatory requirements, scientific and practical issues, and statistical methodology. New to the Second Edition Along with revisions throughout the text
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2
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Design and analysis of experiments / Douglas C Montgomery
Hoboken, New Jersey : John Wiley & Sons, 2017
xv, 734 pages : illustrations ; 26 cm
Ký hiệu phân loại (DDC): 519.57
Design and Analysis of Experiments, 9th Edition continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems.
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Design and analysis of experiments / Douglas C Montgomery
Hoboken, New Jersey : John Wiley & Sons, 2020
x, 550, P-92, A-27, I-2 pages. : illustrations, charts, graphs, tables ; 26 cm.
Ký hiệu phân loại (DDC): 519.57
"Design and Analysis of Experiments provides a rigorous introduction to product and process design improvement through quality and performance optimization. Clear demonstration of widely practiced techniques and procedures allows readers to master fundamental concepts, develop design and analysis skills, and use experimental models and results in real-world applications. Detailed coverage of factorial and fractional factorial design, response surface techniques, regression analysis, biochemistry and biotechnology, single factor experiments, and other critical topics offer highly-relevant guidance through the complexities of the field."
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Design and analysis of experiments /Angela Dean; Daniel Voss; Danel Draguljić
Switzerland : Springer, 2017
Ký hiệu phân loại (DDC): 519.57
This textbook takes a strategic approach to the broad-reaching subject of experimental design by identifying the objectives behind an experiment and teaching practical considerations that govern design and implementation, concepts that serve as the basis for the analytical techniques covered. Rather than a collection of miscellaneous approaches, chapters build on the planning, running, and analyzing of simple experiments in an approach that results from decades of teaching the subject. In most experiments, the procedures can be reproduced by readers, thus giving them a broad exposure to experiments that are simple enough to be followed through their entire course. Outlines of student and published experiments appear throughout the text and as exercises at the end of the chapters. The authors develop the theory of estimable functions and analysis of variance with detail, but at a mathematical level that is simultaneously approachable. Throughout the book, statistical aspects of analysis complement practical aspects of design. This new, second edition includes an additional chapter on computer experiments additional "Using R" sections at the end of each chapter to illustrate R code and output updated output for all SAS programs and use of SAS Proc Mixed new material on screening experiments and analysis of mixed models Angela Dean, PhD, is Professor Emeritus of Statistics and a member of the Emeritus Academy at The Ohio State University, Columbus, Ohio. She is a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Her research interests include design of screening and computer experiments. Daniel Voss, PhD, is Professor Emeritus of Mathematics and Statistics and former Interim Dean of the College of Science and Mathematics at Wright State University, Dayton, Ohio. His research interests include the analysis of saturated fractional factorial experiments, and the equivalence of hypothesis testing and confidence interval estimation. Danel Draguljic, PhD, is Assistant Professor of Mathematics at Franklin & Marshall College, Lancaster, Pennsylvania. His research interests include design of screening experiments, design of computer experiments, and statistics education.
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