An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA |
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| Author:
| Rayner, J. C. W.
Livingston, G. C. |
| Series title: | Wiley Series in Probability and Statistics Ser. |
| ISBN: | 978-1-119-83202-7 |
| Publication Date: | Mar 2023 |
| Publisher: | John Wiley & Sons, Incorporated
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| Book Format: | Digital online |
| List Price: | USD $140.00 |
Book Description:
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An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA Complete reference for applied statisticians and data analysts that uniquely covers the new statistical methodologies that enable deeper data analysis
An 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...
More Description
An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA Complete reference for applied statisticians and data analysts that uniquely covers the new statistical methodologies that enable deeper data analysis
An 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 data
Applied 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.