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Biblioteca

MARC Lista (tabellare)
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (253 p.)
Disciplina 519.5
Altri autori (Persone) KruopisJulius
NikulinM. S (Mikhail Stepanovich)
Collana ISTE
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
Censored observations (Statistics)
ISBN 1-118-55807-3
1-118-60213-7
1-118-60198-X
1-299-18765-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Non-parametric Tests for Censored Data; Title Page; Copyright Page; Table of Contents; Preface; Terms and Notation; Chapter 1. Censored and Truncated Data; 1.1. Right-censored data; 1.2. Left truncation; 1.3. Left truncation and right censoring; 1.4. Nelson-Aalen and Kaplan-Meier estimators; 1.5. Bibliographic notes; Chapter 2. Chi-squared Tests; 2.1. Chi-squared test for composite hypothesis; 2.2. Chi-squared test for exponential distributions; 2.3. Chi-squared tests for shape-scale distribution families; 2.3.1. Chi-squared test for the Weibull distribution
2.3.2. Chi-squared tests for the loglogistic distribution2.3.3. Chi-squared test for the lognormal distribution; 2.4. Chi-squared tests for other families; 2.4.1. Chi-squared test for the Gompertz distribution; 2.4.2. Chi-squared test for distribution with hyperbolic hazard function; 2.4.3. Bibliographic notes; 2.5. Exercises; 2.6. Answers; Chapter 3. Homogeneity Tests for Independent Populations; 3.1. Data; 3.2. Weighted logrank statistics; 3.3. Logrank test statistics as weighted sums of differences between observed and expected number of failures; 3.4. Examples of weights
3.5. Weighted logrank statistics as modified score statistics3.6. The first two moments of weighted logrank statistics; 3.7. Asymptotic properties of weighted logrank statistics; 3.8. Weighted logrank tests; 3.9. Homogeneity testing when alternatives are crossings of survival functions; 3.9.1. Alternatives; 3.9.2. Modified score statistics; 3.9.3. Limit distribution of the modified score statistics; 3.9.4. Homogeneity tests against crossing survival functions alternatives; 3.9.5. Bibliographic notes; 3.10. Exercises; 3.11. Answers; Chapter 4. Homogeneity Tests for Related Populations
4.1. Paired samples4.1.1. Data; 4.1.2. Test statistics; 4.1.3. Asymptotic distribution of the test statistic; 4.1.4. The test; 4.2. Logrank-type tests for homogeneity of related k > 2 samples; 4.3. Homogeneity tests for related samples against crossing marginal survival functions alternatives; 4.3.1. Bibliographic notes; 4.4. Exercises; 4.5. Answers; Chapter 5. Goodness-of-fit for Regression Models; 5.1. Goodness-of-fit for the semi-parametric Cox model; 5.1.1. The Cox model; 5.1.2. Alternatives to the Cox model based on expanded models; 5.1.3. The data and the modified score statistics
5.1.4. Asymptotic distribution of the modified score statistic5.1.5. Tests; 5.2. Chi-squared goodness-of-fit tests for parametric AFT models; 5.2.1. Accelerated failure time model; 5.2.2. Parametric AFT model; 5.2.3. Data; 5.2.4. Idea of test construction; 5.2.5. Asymptotic distribution of Hn and Z; 5.2.6. Test statistics; 5.3. Chi-squared test for the exponential AFT model.; 5.4. Chi-squared tests for scale-shape AFT models.; 5.4.1. Chi-squared test for the Weibull AFT model; 5.4.2. Chi-squared test for the lognormal AFT model; 5.4.3. Chi-squared test for the loglogistic AFT model
5.5. Bibliographic notes
Record Nr. UNINA-9910138865303321
Bagdonavičius V (Vilijandas)  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for censored data [[electronic resource] /] / Vilijandas Bagdonavičius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Edizione [1st ed.]
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (253 p.)
Disciplina 519.5
Altri autori (Persone) KruopisJulius
NikulinM. S (Mikhail Stepanovich)
Collana ISTE
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
Censored observations (Statistics)
ISBN 1-118-55807-3
1-118-60213-7
1-118-60198-X
1-299-18765-X
Classificazione MAT003000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Non-parametric Tests for Censored Data; Title Page; Copyright Page; Table of Contents; Preface; Terms and Notation; Chapter 1. Censored and Truncated Data; 1.1. Right-censored data; 1.2. Left truncation; 1.3. Left truncation and right censoring; 1.4. Nelson-Aalen and Kaplan-Meier estimators; 1.5. Bibliographic notes; Chapter 2. Chi-squared Tests; 2.1. Chi-squared test for composite hypothesis; 2.2. Chi-squared test for exponential distributions; 2.3. Chi-squared tests for shape-scale distribution families; 2.3.1. Chi-squared test for the Weibull distribution
2.3.2. Chi-squared tests for the loglogistic distribution2.3.3. Chi-squared test for the lognormal distribution; 2.4. Chi-squared tests for other families; 2.4.1. Chi-squared test for the Gompertz distribution; 2.4.2. Chi-squared test for distribution with hyperbolic hazard function; 2.4.3. Bibliographic notes; 2.5. Exercises; 2.6. Answers; Chapter 3. Homogeneity Tests for Independent Populations; 3.1. Data; 3.2. Weighted logrank statistics; 3.3. Logrank test statistics as weighted sums of differences between observed and expected number of failures; 3.4. Examples of weights
3.5. Weighted logrank statistics as modified score statistics3.6. The first two moments of weighted logrank statistics; 3.7. Asymptotic properties of weighted logrank statistics; 3.8. Weighted logrank tests; 3.9. Homogeneity testing when alternatives are crossings of survival functions; 3.9.1. Alternatives; 3.9.2. Modified score statistics; 3.9.3. Limit distribution of the modified score statistics; 3.9.4. Homogeneity tests against crossing survival functions alternatives; 3.9.5. Bibliographic notes; 3.10. Exercises; 3.11. Answers; Chapter 4. Homogeneity Tests for Related Populations
4.1. Paired samples4.1.1. Data; 4.1.2. Test statistics; 4.1.3. Asymptotic distribution of the test statistic; 4.1.4. The test; 4.2. Logrank-type tests for homogeneity of related k > 2 samples; 4.3. Homogeneity tests for related samples against crossing marginal survival functions alternatives; 4.3.1. Bibliographic notes; 4.4. Exercises; 4.5. Answers; Chapter 5. Goodness-of-fit for Regression Models; 5.1. Goodness-of-fit for the semi-parametric Cox model; 5.1.1. The Cox model; 5.1.2. Alternatives to the Cox model based on expanded models; 5.1.3. The data and the modified score statistics
5.1.4. Asymptotic distribution of the modified score statistic5.1.5. Tests; 5.2. Chi-squared goodness-of-fit tests for parametric AFT models; 5.2.1. Accelerated failure time model; 5.2.2. Parametric AFT model; 5.2.3. Data; 5.2.4. Idea of test construction; 5.2.5. Asymptotic distribution of Hn and Z; 5.2.6. Test statistics; 5.3. Chi-squared test for the exponential AFT model.; 5.4. Chi-squared tests for scale-shape AFT models.; 5.4.1. Chi-squared test for the Weibull AFT model; 5.4.2. Chi-squared test for the lognormal AFT model; 5.4.3. Chi-squared test for the loglogistic AFT model
5.5. Bibliographic notes
Record Nr. UNINA-9910808680503321
Bagdonavičius V (Vilijandas)  
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Non-parametric tests for complete data / / Vilijandas Bagdonavicius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for complete data / / Vilijandas Bagdonavicius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Pubbl/distr/stampa London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2011
Descrizione fisica xviii, 308 p
Disciplina 519.5
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
ISBN 1-118-60160-2
1-299-18764-1
1-118-55771-9
1-118-60182-3
Classificazione MAT029000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910208835103321
Bagdonavičius V (Vilijandas)  
London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Non-parametric tests for complete data / / Vilijandas Bagdonavicius, Julius Kruopis, Mikhail S. Nikulin
Non-parametric tests for complete data / / Vilijandas Bagdonavicius, Julius Kruopis, Mikhail S. Nikulin
Autore Bagdonavičius V (Vilijandas)
Pubbl/distr/stampa London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2011
Descrizione fisica xviii, 308 p
Disciplina 519.5
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
ISBN 1-118-60160-2
1-299-18764-1
1-118-55771-9
1-118-60182-3
Classificazione MAT029000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910831079703321
Bagdonavičius V (Vilijandas)  
London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Nonparametric hypothesis testing : rank and permutation methods with applications in R / / Stefano Bonnini [and three others]
Nonparametric hypothesis testing : rank and permutation methods with applications in R / / Stefano Bonnini [and three others]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (254 p.)
Disciplina 519.5/4
Collana Wiley Series in Probability and Statistics
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
R (Computer program language)
ISBN 1-118-76349-1
1-118-76347-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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
5.4.2 Permutation test on moments
Record Nr. UNINA-9910132174603321
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Nonparametric hypothesis testing : rank and permutation methods with applications in R / / Stefano Bonnini [and three others]
Nonparametric hypothesis testing : rank and permutation methods with applications in R / / Stefano Bonnini [and three others]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (254 p.)
Disciplina 519.5/4
Collana Wiley Series in Probability and Statistics
Soggetto topico Nonparametric statistics
Statistical hypothesis testing
R (Computer program language)
ISBN 1-118-76349-1
1-118-76347-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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
5.4.2 Permutation test on moments
Record Nr. UNINA-9910812416203321
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Permutation tests for complex data [[electronic resource] ] : theory, applications, and software / / Fortunato Pesarin, Luigi Salmaso
Permutation tests for complex data [[electronic resource] ] : theory, applications, and software / / Fortunato Pesarin, Luigi Salmaso
Autore Pesarin Fortunato
Pubbl/distr/stampa Hoboken, N.J., : Wiley, 2010
Descrizione fisica 1 online resource (450 p.)
Disciplina 519.5
519.5/6
Altri autori (Persone) SalmasoLuigi
Collana Wiley series in probability and statistics
Soggetto topico Statistical hypothesis testing
Permutations
Multivariate analysis
ISBN 1-282-55043-8
9786612550430
0-470-68951-X
0-470-68952-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Permutation 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
1.8.5 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
2 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
2.6 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
3.2.1 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
3.8.1 Basic Notions
Record Nr. UNINA-9910139366203321
Pesarin Fortunato  
Hoboken, N.J., : Wiley, 2010
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Permutation tests for complex data [[electronic resource] ] : theory, applications, and software / / Fortunato Pesarin, Luigi Salmaso
Permutation tests for complex data [[electronic resource] ] : theory, applications, and software / / Fortunato Pesarin, Luigi Salmaso
Autore Pesarin Fortunato
Pubbl/distr/stampa Hoboken, N.J., : Wiley, 2010
Descrizione fisica 1 online resource (450 p.)
Disciplina 519.5
519.5/6
Altri autori (Persone) SalmasoLuigi
Collana Wiley series in probability and statistics
Soggetto topico Statistical hypothesis testing
Permutations
Multivariate analysis
ISBN 1-282-55043-8
9786612550430
0-470-68951-X
0-470-68952-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Permutation 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
1.8.5 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
2 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
2.6 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
3.2.1 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
3.8.1 Basic Notions
Record Nr. UNINA-9910826910103321
Pesarin Fortunato  
Hoboken, N.J., : Wiley, 2010
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Single-case and small-n experimental designs : a practical guide to randomization tests / / Pat Dugard, Portia File, Jonathan Todman
Single-case and small-n experimental designs : a practical guide to randomization tests / / Pat Dugard, Portia File, Jonathan Todman
Autore Dugard Pat.
Edizione [2nd ed.]
Pubbl/distr/stampa New York, N.Y. : , : Routledge Academic, , 2012
Descrizione fisica 1 online resource (xiii, 290 p. ) : ill
Disciplina 519.5/6
Altri autori (Persone) FilePortia
TodmanJohn B
Soggetto topico Statistical hypothesis testing
Experimental design
Soggetto genere / forma Electronic books.
ISBN 1-280-66170-4
9786613638632
0-203-18093-3
1-136-58848-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface. 1. Single-case and Small- n Designs in Context. 2. Understanding Randomization Tests. 3. Obtaining the Data: Choosing the Design. 4. Obtaining the Data: Implementing the Design. 5. Analyzing the Data: Using the Macros. 6. Analyzing the Data: Wider Considerations. 7. Size and Power. 8. Going Further. Appendixes: 1. Basic Skills for Randomization Tests. 2. SPSS Macros. 3. Excel Macros.
Record Nr. UNINA-9910452345503321
Dugard Pat.  
New York, N.Y. : , : Routledge Academic, , 2012
Materiale a stampa
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Single-case and small-n experimental designs : a practical guide to randomization tests / / Pat Dugard, Portia File, Jonathan Todman
Single-case and small-n experimental designs : a practical guide to randomization tests / / Pat Dugard, Portia File, Jonathan Todman
Autore Dugard Pat.
Edizione [2nd ed.]
Pubbl/distr/stampa New York, N.Y. : , : Routledge Academic, , 2012
Descrizione fisica 1 online resource (xiii, 290 p. ) : ill
Disciplina 519.5/6
Altri autori (Persone) FilePortia
TodmanJohn B
Soggetto topico Statistical hypothesis testing
Experimental design
ISBN 1-136-58847-7
1-280-66170-4
9786613638632
0-203-18093-3
1-136-58848-5
Classificazione PSY030000EDU012000MED058200
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface. 1. Single-case and Small- n Designs in Context. 2. Understanding Randomization Tests. 3. Obtaining the Data: Choosing the Design. 4. Obtaining the Data: Implementing the Design. 5. Analyzing the Data: Using the Macros. 6. Analyzing the Data: Wider Considerations. 7. Size and Power. 8. Going Further. Appendixes: 1. Basic Skills for Randomization Tests. 2. SPSS Macros. 3. Excel Macros.
Record Nr. UNINA-9910779016003321
Dugard Pat.  
New York, N.Y. : , : Routledge Academic, , 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui