Permutation Tests
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Permutation Tests
Author: Phillip Good
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
Permutation tests permit us to choose the test statistic best suited to the task at hand. This freedom of choice opens up a thousand practical applications, including many which are beyond the reach of conventional parametric sta tistics. Flexible, robust in the face of missing data and violations of assump tions, the permutation test is among the most powerful of statistical proce dures. Through sample size reduction, permutation tests can reduce the costs of experiments and surveys. This text on the application of permutation tests in biology, medicine, science, and engineering may be used as a step-by-step self-guiding reference manual by research workers and as an intermediate text for undergraduates and graduates in statistics and the applied sciences with a first course in statistics and probability under their belts. Research workers in the applied sciences are advised to read through Chapters 1 and 2 once quickly before proceeding to Chapters 3 through 8 which cover the principal applications they are likely to encounter in practice. Chapter 9 is a must for the practitioner, with advice for coping with real life emergencies such as missing or censored data, after-the-fact covariates, and outliers. Chapter 10 uses practical applications in archeology, biology, climatology, education and social science to show the research worker how to develop new permutation statistics to meet the needs of specific applications. The practitioner will find Chapter 10 a source of inspiration as well as a practical guide to the development of new and novel statistics.
Permutation Tests
Author: Phillip Good
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-04-17
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).
Permutation Tests
Author: Phillip I. Good
language: en
Publisher: Springer Science & Business Media
Release Date: 1994
Permutation tests permit us to choose the test statistic best suited to the task at hand. This freedom of choice opens up a thousand practical applications, including many which are beyond the reach of conventional parametric sta tistics. Flexible, robust in the face of missing data and violations of assump tions, the permutation test is among the most powerful of statistical proce dures. Through sample size reduction, permutation tests can reduce the costs of experiments and surveys. This text on the application of permutation tests in biology, medicine, science, and engineering may be used as a step-by-step self-guiding reference manual by research workers and as an intermediate text for undergraduates and graduates in statistics and the applied sciences with a first course in statistics and probability under their belts. Research workers in the applied sciences are advised to read through Chapters 1 and 2 once quickly before proceeding to Chapters 3 through 8 which cover the principal applications they are likely to encounter in practice. Chapter 9 is a must for the practitioner, with advice for coping with real life emergencies such as missing or censored data, after-the-fact covariates, and outliers. Chapter 10 uses practical applications in archeology, biology, climatology, education and social science to show the research worker how to develop new permutation statistics to meet the needs of specific applications. The practitioner will find Chapter 10 a source of inspiration as well as a practical guide to the development of new and novel statistics.