LEADER 05342nam 2200685 450 001 9910812416203321 005 20221019212513.0 010 $a1-118-76349-1 010 $a1-118-76347-5 035 $a(CKB)3710000000167921 035 $a(EBL)1729067 035 $a(SSID)ssj0001262246 035 $a(PQKBManifestationID)11748161 035 $a(PQKBTitleCode)TC0001262246 035 $a(PQKBWorkID)11216284 035 $a(PQKB)10891299 035 $a(OCoLC)880672189 035 $a(MiAaPQ)EBC1729067 035 $a(Au-PeEL)EBL1729067 035 $a(CaPaEBR)ebr10891171 035 $a(OCoLC)883569926 035 $a(PPN)183860659 035 $a(EXLCZ)993710000000167921 100 $a20140717h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aNonparametric hypothesis testing $erank and permutation methods with applications in R /$fStefano Bonnini [and three others] 210 1$aChichester, England :$cWiley,$d2014. 210 4$dİ2014 215 $a1 online resource (254 p.) 225 1 $aWiley Series in Probability and Statistics 300 $aDescription based upon print version of record. 311 $a1-119-95237-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aNonparametric Hypothesis Testing; Contents; Presentation of the book; Preface; Notation and abbreviations; 1 One- and two-sample location problems, tests for symmetry and tests on a single distribution; 1.1 Introduction; 1.2 Nonparametric tests; 1.2.1 Rank tests; 1.2.2 Permutation tests and combination based tests; 1.3 Univariate one-sample tests; 1.3.1 The Kolmogorov goodness-of-fit test; 1.3.2 A univariate permutation test for symmetry; 1.4 Multivariate one-sample tests; 1.4.1 Multivariate rank test for central tendency; 1.4.2 Multivariate permutation test for symmetry 327 $a1.5 Univariate two-sample tests1.5.1 The Wilcoxon (Mann-Whitney) test; 1.5.2 Permutation test on central tendency; 1.6 Multivariate two-sample tests; 1.6.1 Multivariate tests based on rank; 1.6.2 Multivariate permutation test on central tendency; References; 2 Comparing variability and distributions; 2.1 Introduction; 2.2 Comparing variability; 2.2.1 The Ansari-Bradley test; 2.2.2 The permutation Pan test; 2.2.3 The permutation O'Brien test; 2.3 Jointly comparing central tendency and variability; 2.3.1 The Lepage test; 2.3.2 The Cucconi test; 2.4 Comparing distributions 327 $a2.4.1 The Kolmogorov-Smirnov test2.4.2 The Crame?r-von Mises test; References; 3 Comparing more than two samples; 3.1 Introduction; 3.2 One-way ANOVA layout; 3.2.1 The Kruskal-Wallis test; 3.2.2 Permutation ANOVA in the presence of one factor; 3.2.3 The Mack-Wolfe test for umbrella alternatives; 3.2.4 Permutation test for umbrella alternatives; 3.3 Two-way ANOVA layout; 3.3.1 The Friedman rank test for unreplicated block design; 3.3.2 Permutation test for related samples; 3.3.3 The Page test for ordered alternatives; 3.3.4 Permutation analysis of variance in the presence of two factors 327 $a3.4 Pairwise multiple comparisons3.4.1 Rank-based multiple comparisons for the Kruskal-Wallis test; 3.4.2 Permutation tests for multiple comparisons; 3.5 Multivariate multisample tests; 3.5.1 A multivariate multisample rank-based test; 3.5.2 A multivariate multisample permutation test; References; 4 Paired samples and repeated measures; 4.1 Introduction; 4.2 Two-sample problems with paired data; 4.2.1 The Wilcoxon signed rank test; 4.2.2 A permutation test for paired samples; 4.3 Repeated measures tests; 4.3.1 Friedman rank test for repeated measures 327 $a4.3.2 A permutation test for repeated measuresReferences; 5 Tests for categorical data; 5.1 Introduction; 5.2 One-sample tests; 5.2.1 Binomial test on one proportion; 5.2.2 The McNemar test for paired data (or bivariate responses) with binary variables; 5.2.3 Multivariate extension of the McNemar test; 5.3 Two-sample tests on proportions or 2 x 2 contingency tables; 5.3.1 The Fisher exact test; 5.3.2 A permutation test for comparing two proportions; 5.4 Tests for R x C contingency tables; 5.4.1 The Anderson-Darling permutation test for R x C contingency tables 327 $a5.4.2 Permutation test on moments 330 $aA novel presentation of rank and permutation tests, with accessible guidance to applications in R Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size. < 410 0$aWiley series in probability and statistics. 606 $aNonparametric statistics 606 $aStatistical hypothesis testing 606 $aR (Computer program language) 615 0$aNonparametric statistics. 615 0$aStatistical hypothesis testing. 615 0$aR (Computer program language) 676 $a519.5/4 702 $aBonnini$b Stefano 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910812416203321 996 $aNonparametric hypothesis testing$93944771 997 $aUNINA