[PDF] Permutation Tests eBook

Author : Phillip Good
Publisher : Springer Science & Business Media
Page : 238 pages
File Size : 31,43 MB
Release : 2013-03-09
Category : Mathematics
ISBN : 1475723466

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A step-by-step guide to the application of permutation tests in biology, medicine, science, and engineering. The intuitive and informal style makes this manual ideally suitable for students and researchers approaching these methods for the first time. In particular, it shows how to handle the problems of missing and censored data, nonresponders, after-the-fact covariates, and outliers.

Author : Fortunato Pesarin
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 40,85 MB
Release : 2010-02-25
Category : Mathematics
ISBN : 9780470689523

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Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies. The Authors give a general overview on permutation tests with a focus on recent theoretical advances within univariate and multivariate complex permutation testing problems, this book brings the reader completely up to date with today’s current thinking. Key Features: Examines the most up-to-date methodologies of univariate and multivariate permutation testing. Includes extensive software codes in MATLAB, R and SAS, featuring worked examples, and uses real case studies from both experimental and observational studies. Includes a standalone free software NPC Test Release 10 with a graphical interface which allows practitioners from every scientific field to easily implement almost all complex testing procedures included in the book. Presents and discusses solutions to the most important and frequently encountered real problems in multivariate analyses. A supplementary website containing all of the data sets examined in the book along with ready to use software codes. Together with a wide set of application cases, the Authors present a thorough theory of permutation testing both with formal description and proofs, and analysing real case studies. Practitioners and researchers, working in different scientific fields such as engineering, biostatistics, psychology or medicine will benefit from this book.

Author : Dario Basso
Publisher : Springer Science & Business Media
Page : 223 pages
File Size : 17,80 MB
Release : 2009-04-20
Category : Mathematics
ISBN : 038785956X

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Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents new advanced methods and related R codes to perform complex multivariate analyses. The prerequisites are a standard course in statistics and some background in multivariate analysis and R software.

Author : Phillip I. Good
Publisher : Springer Science & Business Media
Page : 296 pages
File Size : 31,20 MB
Release : 2000
Category : Mathematics
ISBN :

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This book provides a step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering. The first edition of this book is well known for its intuitive and informal style, and the inclusion of numerous real-world problems. This new edition has more than l00 additional pages, and includes streamlined statistics for the k-sample comparison and analysis of variance plus expanded sections on computational techniques, multiple comparisons, multiple regression, comparing variances, and testing interactions in balanced designs.

Author : Fortunato Pesarin
Publisher : Wiley
Page : 432 pages
File Size : 26,99 MB
Release : 2001-06-08
Category : Mathematics
ISBN : 9780471496700

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Complex multivariate problems are frequently encountered in many scientific disciplines and it can be very difficult to obtain meaningful results. Permutation and nonparametric combination methods provide flexible solutions to complex problems by reducing the problem down to a set of simpler sub-problems. The author presents a novel but well tested approach using real examples taken from biomedical research. Statistical analyses are performed in a nonparametric setting, so that no assumptions need be made about the underlying distribution and the dependence relations between variables. * Provides a clear exposition of the use of multivariate permutation testing, with emphasis on the use of nonparametric combination methodology. * Growing area of research with many practical applications, notably in biostatistics. * Numerous case studies and examples help to illustrate the theory. * Provides solutions to multi-aspect problems, to problems with missing data, analysis of factorial designs and repeated measures. * Explains the analysis of categorical, ordered categorical, binary, continuous, and mixed variables in both an experimental and an observational context. * NPC-Test(c) software (demo copy), SAS macros, S-Plus code and datasets are available on the Web at http://www.stat.unipd.it/~pesarin/ For researchers and practitioners in a number of scientific disciplines, particularly biostatistics, the vast collection of techniques, examples and case studies will be an invaluable resource. Graduate students of applied statistics and nonparametric methods will find the book provides an accessible introduction to multivariate permutation testing.

Author : LUIGI SALMASO
Publisher : Springer Science & Business Media
Page : 105 pages
File Size : 11,59 MB
Release : 2013-09-06
Category : Mathematics
ISBN : 1461481635

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Statistical shape analysis is a geometrical analysis from a set of shapes in which statistics are measured to describe geometrical properties from similar shapes or different groups, for instance, the difference between male and female Gorilla skull shapes, normal and pathological bone shapes, etc. Some of the important aspects of shape analysis are to obtain a measure of distance between shapes, to estimate average shapes from a (possibly random) sample and to estimate shape variability in a sample[1]. One of the main methods used is principal component analysis. Specific applications of shape analysis may be found in archaeology, architecture, biology, geography, geology, agriculture, genetics, medical imaging, security applications such as face recognition, entertainment industry (movies, games), computer-aided design and manufacturing. This is a proposal for a new Brief on statistical shape analysis and the various new parametric and non-parametric methods utilized to facilitate shape analysis. ​ ​

Author : Phillip I. Good
Publisher : Springer Science & Business Media
Page : 331 pages
File Size : 13,58 MB
Release : 2005-12-19
Category : Mathematics
ISBN : 0387271589

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Previous edition sold over 1400 copies worldwide. This new 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.

Author : Phillip Good
Publisher : Springer Science & Business Media
Page : 288 pages
File Size : 27,9 MB
Release : 2013-04-17
Category : Mathematics
ISBN : 147573235X

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A step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering. Its intuitive and informal style make it ideal for students and researchers, whether experienced or coming to these resampling methods for the first time. The real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are all dealt with at length. This new edition has more than 100 additional pages, and includes streamlined statistics for the k-sample comparison and analysis of variance plus expanded sections on computational techniques, multiple comparisons, multiple regression, comparing variances, and testing interactions in balanced designs. The comprehensive author and subject indexes, plus an expert-system guide to methods, provide for further ease of use, while the exercises at the end of every chapter have been supplemented with drills and a number of graduate-level thesis problems.

Author : Luigi Salmaso
Publisher : Springer Science & Business Media
Page : 75 pages
File Size : 34,69 MB
Release : 2011-07-09
Category : Medical
ISBN : 3642205844

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The purpose of this book is to illustrate a new statistical approach to test allelic association and genotype-specific effects in the genetic study of diseases. There are some parametric and non-parametric methods available for this purpose. We deal with population-based association studies, but comparisons with other methods will also be drawn, analysing the advantages and disadvantages of each one, particularly with regard to power properties with small sample sizes. In this framework we will work out some nonparametric statistical permutation tests and likelihood-based tests to perform case-control analyses to study allelic association between marker, disease-gene and environmental factors. Permutation tests, in particular, will be extended to multivariate and more complex studies, where we deal with several genes and several alleles together. Furthermore, we show simulations under different assumptions on the genetic model and analyse real data sets by simply studying one locus with the permutation test.

Author : Eugene Edgington
Publisher : CRC Press
Page : 444 pages
File Size : 14,81 MB
Release : 1995-07-25
Category : Mathematics
ISBN : 9780824796693

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The material in this work is organized in such as way as to illustrate how randomization tests are related to topics in parametric and traditional nonparametric statistics. The work extends the scope of applications by freeing tests from parametric assumptions without reducing data to ranks. This edition provides many new features, including more accessible terminology to clarify understanding, a current analysis of single-unit experiments as well as single-subject experiments, a discussion on how single-subject experiments relate to repeated-measures experiments and the use of randomized tests in single-patient research, and more.