Phillip Good Good Permutation Tests

Permutation Tests

von Phillip Good

A Practical Guide to Resampling Methods for Testing Hypotheses

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Beschreibung

This text will equip both practitioners and theorists with the necessary background in testing hypothesis and decision theory to enable innumerable practical applications of statistics. Its intuitive and informal style makes it suitable as a text for both students and researchers. It can serve as the basis a one- or two-semester graduate course as well as a standard handbook of statistical procedures for the practitioners’ desk. Parametric, permutation, and bootstrap procedures for testing hypotheses are developed side by side. The emphasis on distribution-free permutation procedures will enable workers in applied fields to use the most powerful statistic for their applications and satisfy regulatory agency demands for methods that yield exact significance levels, not approximations. Algebra and an understanding of discrete probability will take the reader through all but the appendix, which utilizes probability measures in its proofs. The revised and expanded text of the 3rd edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. Real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length. New sections are added on sequential analysis and multivariate analysis plus a chapter on the exact analysis of multi-factor designs based on the recently developed theory of synchronous permutations.  The book's main features include: Detailed consideration of one-, two-, and k-sample tests, contingency tables, clinical trials, cluster analysis, multiple comparisons, multivariate analysis, and repeated measures Numerous practical applications in archeology, biology, business, climatology, clinical trials, economics, education, engineering, geology, law, medicine, and the social sciences Valuable techniques for reducing computation time Practical advice on experimental design Sections on sequential analysis Comparisons among competing bootstrap, parametric, and permutation techniques.  From a review of the first edition: "Permutation Tests is a welcome addition to the literature on this subject and will prove a valuable guide for practitioners . . . This book has already become an important addition to my reference library. Those interested in permutation tests and its applications will enjoy reading it." (Journal of the American Statistical Association) From a review of the second edition: "Permutation Tests is superb as a resource for practitioners. The text covers a broad range of topics, and has myriad pointers to topics not directly addressed. . . the book gives guidance and inspiration to encourage developing one’s own perfectly tailored statistics…The writing is fun to read." (John I. Marden)
In 1982, I published several issues of a samdizat scholarly journal called Random ization with the aid of an 8-bit, I-MH personal computer with 48K of memory (upgraded to 64K later that year) and floppy disks that held 400 Kbytes. A decade later, working on the first edition of this text, I used a 16-bit, 33-MH computer with 1 Mb of memory and a 20-Mb hard disk. This preface to the second edition comes to you via a 32-bit, 300-MH computer with 64-Mb memory and a 4-Gb hard disk. And, yes, I paid a tenth of what I paid for my first computer. This relationship between low-cost readily available computing power and the rising popularity of permutation tests is no coincidence. Simply put, it is" faster today to compute an exact p-value than to look up an approximation in a table of the not-quite-appropriate statistic. As a result, more and more researchers are using Permutation Tests to analyze their data. Of course, some of the increased usage has also come about through the increased availability of and improvements in off-the-shelf software, as can be seen in the revisions in this edition to Chapter 12 (Publishing Your Results) and Chapter 13 (Increasing Computation Efficiency).

Contains valuable techniques for reducing computation time, practical advice on experimental design, comparisons with bootstrap, parametric, and nonparametric techniques and a three-part bibliography featuring more than 1,000 articles


This text will equip both practitioners and theorists with the necessary background in testing hypothesis and decision theory to enable innumerable practical applications of statistics. The revised and expanded text of the third edition includes many more real-world illustrations from biology, business, clinical trials, economics, geology, law, medicine, social science and engineering along with twice the number of exercises. Real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are dealt with at length.



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Phillip Good

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Multiple Regression Resampling analysis of variance calculus cluster analysis efficiency permutation tests statistics

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From a review of the first edition:
"Permutation Tests is a welcome addition to the literature on this subject and will prove a valuable guide for practitioners...This book has already become an important addition to my reference library. Those interested in permutation tests and its applications will enjoy reading it."
Journal of the American Statistical Association

Review of the third edition:

"The book has been considerably reorganized and extensively rewritten from the 1E and the second edition...Although it is larger by only 30 pages, it is still a much different book." Technometrics, November 2005


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Details

ISBN: 9780387988986
Verlag: Springer US
Erscheinung: 27.01.2000

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