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Author: Fortunato Pesarin
Publisher: John Wiley & Sons
ISBN: 9780470689523
Category : Mathematics
Languages : en
Pages : 448
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Book Description
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: Fortunato Pesarin
Publisher: John Wiley & Sons
ISBN: 9780470689523
Category : Mathematics
Languages : en
Pages : 448
Get Book Here
Book Description
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: Phillip Good
Publisher: Springer Science & Business Media
ISBN: 1475723466
Category : Mathematics
Languages : en
Pages : 238
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Book Description
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: Phillip I. Good
Publisher: Springer Science & Business Media
ISBN:
Category : Mathematics
Languages : en
Pages : 296
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Book Description
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: Dario Basso
Publisher: Springer Science & Business Media
ISBN: 038785956X
Category : Mathematics
Languages : en
Pages : 223
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Book Description
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: Fortunato Pesarin
Publisher: Wiley
ISBN: 9780471496700
Category : Mathematics
Languages : en
Pages : 432
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Book Description
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: Sean P. Sullivan
Publisher:
ISBN:
Category : Experimental economics
Languages : en
Pages : 0
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Book Description
This article surveys the use of nonparametric permutation tests for analyzing experimental data. The permutation approach, which involves randomizing or permuting features of the observed data, is a flexible way to draw statistical inferences in common experimental settings. It is particularly valuable when few independent observations are available, a frequent occurrence in controlled experiments in economics and other social sciences. The permutation method constitutes a comprehensive approach to statistical inference. In two-treatment testing, permutation concepts underlie popular rank-based tests, like the Wilcoxon and Mann–Whitney tests. But permutation reasoning is not limited to ordinal contexts. Analogous tests can be constructed from the permutation of measured observations—as opposed to rank-transformed observations—and we argue that these tests should often be preferred. Permutation tests can also be used with multiple treatments, with ordered hypothesized effects, and with complex data-structures, such as hypothesis testing in the presence of nuisance variables. Drawing examples from the experimental economics literature, we illustrate how permutation testing solves common challenges. Our aim is to help experimenters move beyond the handful of overused tests in play today and to instead see permutation testing as a flexible framework for statistical inference.
Author: Luigi Salmaso
Publisher: Springer
ISBN: 9781461481621
Category : Mathematics
Languages : en
Pages : 0
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Book Description
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: Springer
Publisher:
ISBN: 9781475732368
Category :
Languages : en
Pages : 292
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Book Description
Author: Paul W. Mielke (jr.)
Publisher: Springer Science & Business Media
ISBN: 9780387988825
Category : Mathematics
Languages : en
Pages : 384
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Book Description
The book will provide a comprehensive treatment of statistical inference using permutation techniques. Its purpose is to make available to practitioners a variety of useful and powerful data analytic tools that rely on very few distributional assumptions. Although many of these procedures have appeared in journal articles, they are not readily available to practitioners.
Author: Stefano Bonnini
Publisher: John Wiley & Sons
ISBN: 1118763483
Category : Mathematics
Languages : en
Pages : 242
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Book Description
A novel presentation of rank and permutation tests, with accessible guidance to applications in R Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size. Key Features: Examines the most widely used methodologies of nonparametric testing. Includes extensive software codes in R featuring worked examples, and uses real case studies from both experimental and observational studies. Presents and discusses solutions to the most important and frequently encountered real problems in different fields. Features a supporting website (www.wiley.com/go/hypothesis_testing) containing all of the data sets examined in the book along with ready to use R software codes. Nonparametric Hypothesis Testing combines an up to date overview with useful practical guidance to applications in R, and will be a valuable resource for practitioners and researchers working in a wide range of scientific fields including engineering, biostatistics, psychology and medicine.
