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Introduction to Modern Nonparametric Statistics By James J. Higgins

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Review
1. ONE-SAMPLE METHODS. Preliminaries. A Nonparametric Test and Confidence Interval for the Median. Estimating the Population CDF and Quantiles. A Comparison of Statistical Tests. 2. TWO-SAMPLE METHODS. A Two-Sample Permutation Test. Permutation Tests Based on the Median and Trimmed Means. Random Sampling the Permutations. Wilcoxon Rank-Sum Test. Wilcoxon Rank-Sum Test Adjusted for Ties. Mann-Whitney Test and a Confidence Interval. Scoring Systems. Test for Equality of Scale Parameters and an Omnibus Test. Selecting Among Two-Sample Tests. Large Sample Approximations. Exercises. 3. K-SAMPLE METHODS. K-Sample Permutation Tests. The Kruskal-Wallis Test. Multiple Comparisons. Ordered Alternatives. Exercises. 4. PAIRED COMPARISONS AND BLOCKED DESIGNS. Paired Comparison Permutation Test. Signed-Rank Test. Other Paired-Comparison Tests. A Permutation Test for a Randomized Complete Block Design. Friedman's Test for a Randomized Complete Block Design. Ordered Alternatives for a Randomized Complete Block Design. Exercises. 5. TESTS FOR TRENDS AND ASSOCIATION. A Permutation Test for Correlation and Slope. Spearman Rank Correlation. Kendall's Tau. Permutation Tests for Contingency Tables. Fisher's Exact Test for a 2 ?e 2 Contingency Table. Contingency Tables With Ordered Categories. Mantel-Haenszel Test. Exercises. 6. MULTIVARIATE TESTS. Two-Sample Multivariate Permutation Tests. Two-Sample Multivariate Rank Tests. Multivariate Paired Comparisons. Multivariate Rank Tests for Paired Comparisons. Multi-response Categorical Data. Exercises. 7. ANALYSIS OF CENSORED DATA. Estimating the Survival Function. Permutation Tests for Two-Sample Censored Data. Gehan's Generalization of the Mann-Whitney-Wilcoxon Test. Scoring Systems for Censored Data. Tests Using Scoring Systems for Censored Data. Exercises. 8. NONPARAMETRIC BOOTSTRAP METHODS. The Basic Bootstrap Method. Bootstrap Intervals for Location-Scale Models. BCA and Other Bootstrap Intervals. Correlation and Regression. Two-Sample Inference. Bootstrap Sampling from Several Populations. Bootstrap Sampling for Multiple Regression. Multivariate Bootstrap Sampling. Exercises. 9. MULTIFACTOR EXPERIMENTS. Analysis of Variance Models. Aligned Rank Transform. Testing for Lattice-Ordered Alternatives. Exercises. 10. SMOOTHING METHODS AND ROBUST MODEL FITTING. Estimating the Probability Density Function. Nonparametric Curve Smoothing. Robust and Rank-Based Regression. Exercises. TABLES. REFERENCES.
About the Author
James J. Higgins is Professor of Statistics at Kansas State University and Fellow of the American Statistical Association. He is the co-author of the Duxbury textbook CONCEPTS IN PROBABILITY AND STOCHASTIC MODELING with Sallie Keller-McNulty and he is author of INTRODUCTION TO MODERN NONPARAMETRIC STATISTICS as well as having over 80 scientific publications to his credit. In addition, he is a statistical consultant for Kansas State Research and Extension. His research interests include nonparametric statistics and reliability theory.
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