Overview
- Examines properties of robust estimators and their relative merits
- Focuses on heteroscedastic techniques, including recent advances dealing multicollinearity
- Contains recent advances dealing with measures effect size and outliers, including bad leverage points
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true—but they continue to perform well in situations where classic methods perform poorly.
This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.
The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
Authors and Affiliations
About the author
Rand R. Wilcox is Professor of Psychology, USC Dornsife College of Letters, Arts and Sciences. He has written 15 other statistics books, including Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy, 2nd edition (2010), over 400 journal articles, is a former associate editor for 5 statistics journals, is an elected member of the International Statistical Institute and he created the R package, WRS.
Bibliographic Information
Book Title: A Guide to Robust Statistical Methods
Authors: Rand R. Wilcox
DOI: https://doi.org/10.1007/978-3-031-41713-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-41712-2Published: 26 October 2023
Softcover ISBN: 978-3-031-41715-3Due: 26 November 2023
eBook ISBN: 978-3-031-41713-9Published: 25 October 2023
Edition Number: 1
Number of Pages: XVII, 326
Number of Illustrations: 57 b/w illustrations
Topics: Statistical Theory and Methods, Applied Statistics, Statistics, general