Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful 'how-to' on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity that can provide substantial gains in power. Coverage includes techniques for comparing groups and measuring effect size, current methods for comparing quantiles, and expanded regression methods for both parametric and nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are included to support comprehension and practice.
Table of Contents
1. Introduction 2. A Foundation for Robust Methods 3. Estimating Measures of Location and Scale 4. Confidence Intervals in the One-Sample Case 5. Comparing Two Groups 6. Some Multivariate Methods 7. One-Way and Higher Designs for Independent Groups 8. Comparing Multiple Dependent Groups 9. Correlation and Tests of Independence 10. Robust Regression 11. More Regression Methods 12. ANCOVA
