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Produktbild: Permutation Tests for Complex Data

Permutation Tests for Complex Data Theory, Applications and Software

Aus der Reihe Wiley Series in Probability and Statistics

Fr. 179.00

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

19.03.2010

Verlag

John Wiley & Sons Inc

Seitenzahl

448

Maße (L/B/H)

22.9/15.2/2.9 cm

Gewicht

876 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-51641-6

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

19.03.2010

Verlag

John Wiley & Sons Inc

Seitenzahl

448

Maße (L/B/H)

22.9/15.2/2.9 cm

Gewicht

876 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-51641-6

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  • Produktbild: Permutation Tests for Complex Data
  • Contents
     
    Preface

    Notation and Abbreviations

    1 Introduction
     
    1.1 On Permutation Analysis
     
    1.2 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
     
    1.9 The Permutation Solution
     
    1.10 A Two-Sample Problem
     
    1.11 One-Way ANOVA

    2 Theory of One-Dimensional Permutation Tests
     
    2.1 Introduction
     
    2.2 Definition of Permutation Tests
     
    2.3 Some Useful Test Statistics
     
    2.4 Equivalence of Permutation Statistics
     
    2.5 Arguments for Selecting Permutation Tests
     
    2.6 Examples of One-Sample Problems
     
    2.7 Examples of Multi-sample Problems
     
    2.8 Analysis of Ordered Categorical Variables
     
    2.9 Problems and Exercises

    3 Further Properties of Permutation Tests
     
    3.1 Unbiasedness of Two-sample Tests
     
    3.2 Power Functions of Permutation Tests
     
    3.3 Consistency of Permutation Tests
     
    3.4 Permutation Confidence Interval for ´
     
    3.5 Extending Inference from Conditional to Unconditional
     
    3.6 Optimal Properties
     
    3.7 Some Asymptotic Properties
     
    3.8 Permutation Central Limit Theorems
     
    3.9 Problems and Exercises

    4 The Nonparametric Combination Methodology
     
    4.1 Introduction
     
    4.2 The Nonparametric Combination Methodology
     
    4.3 Consistency, Unbiasedness and Power of Combined Tests
     
    4.4 Some Further Asymptotic Properties
     
    4.5 Finite-Sample Consistency
     
    4.6 Some Examples of Nonparametric Combination
     
    4.7 Comments on the Nonparametric Combination

    5 Multiple Testing Problems and Multiplicity Adjustment
     
    5.1 Defining Raw and Adjusted p-Values
     
    5.2 Controlling for Multiplicity
     
    5.3 Multiple Testing
     
    5.4 The Closed Testing Approach
     
    5.5 Mult Data Example
     
    5.6 Washing Test Data
     
    5.7 Weighted Methods for Controlling FWE and FDR
     
    5.8 Adjusting Stepwise p-Values

    6 Analysis of Multivariate Categorical Variables
     
    6.1 Introduction
     
    6.2 The Multivariate McNemar Test
     
    6.3 Multivariate Goodness-of-Fit Testing for Ordered Variables
     
    6.4 MANOVA with Nominal Categorical Data
     
    6.5 Stochastic Ordering
     
    6.6 Multifocus Analysis
     
    6.7 Isotonic Inference
     
    6.8 Test on Moments for Ordered Variables
     
    6.9 Heterogeneity Comparisons
     
    6.10 Application to PhD Programme Evaluation Using SAS

    7 Permutation Testing for Repeated Measurements
     
    7.1 Introduction
     
    7.2 Carry-Over Effects in Repeated Measures Designs
     
    7.3 Modelling Repeated Measurements
     
    7.4 Testing Solutions
     
    7.5 Testing for Repeated Measurements with Missing Data
     
    7.6 General Aspects of Permutation Testing with Missing Data
     
    7.7 On Missing Data Processes
     
    7.8 The Permutation Approach
     
    7.9 The Structure of Testing Problems
     
    7.10 Permutation Analysis of Missing Values
     
    7.11 Germina Data: An Example of an MNAR Model
     
    7.12 Multivariate Paired Observations
     
    7.13 Repeated Measures and Missing Data
     
    7.14 Botulinum Data
     
    7.15 Waterfalls Data

    8 Some Stochastic Ordering Problems
     
    8.1 Multivariate Ordered Alternatives
     
    8.2 Testing for Umbrella Alternatives
     
    8.3 Analysis of Expe