Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA

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A01=G. C. Livingston
A01=J. C. W. Rayner
applied statistics
Author_G. C. Livingston
Author_J. C. W. Rayner
balanced incomplete block designs
Category=PB
CMH MS tests
Cochran-Mantel-Haenszel (CMH) methodology and design
data analysis
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Jr.
Latin squares
nonparametric analysis of categorical response data
Nonparametric rank tests
NP ANOVA methodology
Parametric ANOVA F tests
r code
the Friedman tests
the Kruskal-Wallis tests

Product details

  • ISBN 9781119831983
  • Weight: 482g
  • Dimensions: 170 x 244mm
  • Publication Date: 23 Mar 2023
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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 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.

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.

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