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Informationen zum Autor John Charles William Rayner is an Honorary Professorial Fellow, National Institute for Applied Statistics Research Australia, University of Wollongong, and Conjoint Professor of Statistics, School of Mathematical and Physical Sciences, University of Newcastle, Australia. Glen Livingston, Jr., is a Lecturer, School of Mathematical and Physical Sciences, University of Newcastle, Australia. Klappentext An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVAComplete reference for applied statisticians and data analysts that uniquely covers the new statistical methodologies that enable deeper data analysisAn Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA provides readers with powerful new statistical methodologies that enable deeper data analysis. The book offers applied statisticians an introduction to the latest topics in nonparametrics. The worked examples with supporting R code provide analysts the tools they need to apply these methods to their own problems.Co-authored by an internationally recognised expert in the field and an early career researcher with broad skills including data analysis and R programming, the book discusses key topics such as:* NP ANOVA methodology* Cochran-Mantel-Haenszel (CMH) methodology and design* Latin squares and balanced incomplete block designs* Parametric ANOVA F tests for continuous data* Nonparametric rank tests (the Kruskal-Wallis and Friedman tests)* CMH MS tests for the nonparametric analysis of categorical response dataApplied statisticians and data analysts, as well as students and professors in data analysis, can use this book to gain a complete understanding of the modern statistical methodologies that are allowing for deeper data analysis. Zusammenfassung An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVAComplete reference for applied statisticians and data analysts that uniquely covers the new statistical methodologies that enable deeper data analysisAn Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA provides readers with powerful new statistical methodologies that enable deeper data analysis. The book offers applied statisticians an introduction to the latest topics in nonparametrics. The worked examples with supporting R code provide analysts the tools they need to apply these methods to their own problems.Co-authored by an internationally recognised expert in the field and an early career researcher with broad skills including data analysis and R programming, the book discusses key topics such as:* NP ANOVA methodology* Cochran-Mantel-Haenszel (CMH) methodology and design* Latin squares and balanced incomplete block designs* Parametric ANOVA F tests for continuous data* Nonparametric rank tests (the Kruskal-Wallis and Friedman tests)* CMH MS tests for the nonparametric analysis of categorical response dataApplied statisticians and data analysts, as well as students and professors in data analysis, can use this book to gain a complete understanding of the modern statistical methodologies that are allowing for deeper data analysis. Inhaltsverzeichnis Preface xiii 1 Introduction 1 1.1 What are the CMH and NP ANOVA tests? 1 1.2 Outline 3 1.3 5 1.4 Examples 6 2 The Basic CMH Tests 13 2.1 Genesis: Cochran (1954), and Mantel and Haenszel (1959) 13 2.2 The basic CMH tests 18 2.3 The Nominal CMH tests 22 2.4 The CMH mean scores test 26 2.5 The CMH correlation test 28 3 The Completely Randomised Design 41 3.1 Introduction 41 3.2 The design and parametric model 42 3.3 The Kruskal-Wallis tests 43 3.4 Relating the Kruskal-Wallis and ANOVA F tests 47 3.5 The CMH tests for the CRD 49 3.6 The KW tests are CMH MS tests 52 3.7 Relating the ...
