LEADER 05404nam 2200673Ia 450 001 9910826910103321 005 20230725041552.0 010 $a1-282-55043-8 010 $a9786612550430 010 $a0-470-68951-X 010 $a0-470-68952-8 035 $a(CKB)2520000000006742 035 $a(EBL)496063 035 $a(OCoLC)605024824 035 $a(SSID)ssj0000364252 035 $a(PQKBManifestationID)11263860 035 $a(PQKBTitleCode)TC0000364252 035 $a(PQKBWorkID)10398970 035 $a(PQKB)10608754 035 $a(MiAaPQ)EBC496063 035 $a(EXLCZ)992520000000006742 100 $a20100125d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPermutation tests for complex data$b[electronic resource] $etheory, applications, and software /$fFortunato Pesarin, Luigi Salmaso 210 $aHoboken, N.J. $cWiley$d2010 215 $a1 online resource (450 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a0-470-51641-0 320 $aIncludes bibliographical references and index. 327 $aPermutation Tests for Complex Data; Contents; Preface; Notation and Abbreviations; 1 Introduction; 1.1 On Permutation Analysis; 1.2 The Permutation Testing Principle; 1.2.1 Nonparametric Family of Distributions; 1.2.2 The Permutation Testing Principle; 1.3 Permutation Approaches; 1.4 When and Why Conditioning is Appropriate; 1.5 Randomization and Permutation; 1.6 Computational Aspects; 1.7 Basic Notation; 1.8 A Problem with Paired Observations; 1.8.1 Modelling Responses; 1.8.2 Symmetry Induced by Exchangeability; 1.8.3 Further Aspects; 1.8.4 The Student's t-Paired Solution 327 $a1.8.5 The Signed Rank Test Solution1.8.6 The McNemar Solution; 1.9 The Permutation Solution; 1.9.1 General Aspects; 1.9.2 The Permutation Sample Space; 1.9.3 The Conditional Monte Carlo Method; 1.9.4 Approximating the Permutation Distribution; 1.9.5 Problems and Exercises; 1.10 A Two-Sample Problem; 1.10.1 Modelling Responses; 1.10.2 The Student t Solution; 1.10.3 The Permutation Solution; 1.10.4 Rank Solutions; 1.10.5 Problems and Exercises; 1.11 One-Way ANOVA; 1.11.1 Modelling Responses; 1.11.2 Permutation Solutions; 1.11.3 Problems and Exercises 327 $a2 Theory of One-Dimensional Permutation Tests2.1 Introduction; 2.1.1 Notation and Basic Assumptions; 2.1.2 The Conditional Reference Space; 2.1.3 Conditioning on a Set of Sufficient Statistics; 2.2 Definition of Permutation Tests; 2.2.1 General Aspects; 2.2.2 Randomized Permutation Tests; 2.2.3 Non-randomized Permutation Tests; 2.2.4 The p-Value; 2.2.5 A CMC Algorithm for Estimating the p-Value; 2.3 Some Useful Test Statistics; 2.4 Equivalence of Permutation Statistics; 2.4.1 Some Examples; 2.4.2 Problems and Exercises; 2.5 Arguments for Selecting Permutation Tests 327 $a2.6 Examples of One-Sample Problems2.6.1 A Problem with Repeated Observations; 2.6.2 Problems and Exercises; 2.7 Examples of Multi-Sample Problems; 2.8 Analysis of Ordered Categorical Variables; 2.8.1 General Aspects; 2.8.2 A Solution Based on Score Transformations; 2.8.3 Typical Goodness-of-Fit Solutions; 2.8.4 Extension to Non-Dominance Alternatives and C Groups; 2.9 Problems and Exercises; 3 Further Properties of Permutation Tests; 3.1 Unbiasedness of Two-sample Tests; 3.1.1 One-Sided Alternatives; 3.1.2 Two-Sided Alternatives; 3.2 Power Functions of Permutation Tests 327 $a3.2.1 Definition and Algorithm for the Conditional Power3.2.2 The Empirical Conditional ROC Curve; 3.2.3 Definition and Algorithm for the Unconditional Power: Fixed Effects; 3.2.4 Unconditional Power: Random Effects; 3.2.5 Comments on Power Functions; 3.3 Consistency of Permutation Tests; 3.4 Permutation Confidence Interval for d; 3.4.1 Problems and Exercises; 3.5 Extending Inference from Conditional to Unconditional; 3.6 Optimal Properties; 3.6.1 Problems and Exercises; 3.7 Some Asymptotic Properties; 3.7.1 Introduction; 3.7.2 Two Basic Theorems; 3.8 Permutation Central Limit Theorems 327 $a3.8.1 Basic Notions 330 $aComplex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies. The Authors give a general overview on permutation tests with a focus on recent theoretical advances within univariate and multivariate complex permutation testing problems, this book brings the reader completely up to date with today's current thinking. Key Features:Examines the mos 410 0$aWiley series in probability and statistics. 606 $aStatistical hypothesis testing 606 $aPermutations 606 $aMultivariate analysis 615 0$aStatistical hypothesis testing. 615 0$aPermutations. 615 0$aMultivariate analysis. 676 $a519.5 676 $a519.5/6 700 $aPesarin$b Fortunato$0103222 701 $aSalmaso$b Luigi$0741086 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910826910103321 996 $aPermutation tests for complex data$91470379 997 $aUNINA