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Nonparametric hypothesis testing : rank and permutation methods with applications in R /
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...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chichester, West Sussex :
John Wiley & Sons,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Nonparametric 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.
- 1.5 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.
- 2.4.1 The Kolmogorov-Smirnov test2.4.2 The Cramér-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.
- 3.4 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.
- 4.3.2 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.