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＜電子ブック＞
Permutation Methods : A Distance Function Approach / by Paul W. Mielke, Kenneth J. Berry
(Springer Series in Statistics. ISSN:2197568X)

版	2nd ed. 2007.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2007
本文言語	英語
大きさ	XVIII, 446 p : online resource
著者標目	*Mielke, Paul W author Berry, Kenneth J author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Statistics  LCSH:Biometric identification LCSH:Data mining LCSH:Psychometrics LCSH:Public health FREE:Probability Theory FREE:Statistical Theory and Methods FREE:Biometrics FREE:Data Mining and Knowledge Discovery FREE:Psychometrics FREE:Public Health
一般注記	Description of MRPP -- Additional MRPP Applications -- Description of MRBP -- Regression Analysis, Prediction, and Agreement -- Goodness-of-Fit Tests -- Contingency Tables -- Multisample Homogeneity Tests -- Selected Permutation Studies Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses. In addition to permutation techniques described in the first edition, this second edition also contains various new permutation statistical methods and studies that include resampling multiple contingency table analyses, analysis concerns involving log-linear models with small samples, an exact discrete analog of Fisher’s continuous method for combining P-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisher’s Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of two samples. Paul W. Mielke, Jr. is Professor of Statistics at Colorado State University, and a fellow of the American Statistical Association. Kenneth J. Berry is Professor of Sociology at Colorado State University HTTP:URL=https://doi.org/10.1007/978-0-387-69813-7

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