Автор: J.C.W. Rayner, G.C. Livingston Jr.
Издательство: Wiley
Серия: Wiley Series in Probability and Statistics
Год: 2023
Страниц: 243
Язык: английский
Формат: pdf (true), epub
Размер: 34.4 MB
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.
We have written an R package called CMHNPA, which will serve as an accompaniment to this text. The package contains all the data sets which are analysed as well as functions written for the statistical methods and techniques discussed. Within each of the chapters there is R code where example data sets are used. If the output from the functions is excessive, it will sometimes be suppressed; however, the code will be presented for the reader to execute the functions themselves.
All of the code that follows in this text has the type of code shown above omitted. Therefore, if the reader wishes to recreate the output in later chapters, the packages will need to be loaded, and the data set attached to the workspace. The R package is currently available from Cran. It will undergo ongoing development and so output of functions may change and additional options added for functions over time.
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.
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