Nonparametric methods in statistics with SAS applications / Olga Korosteleva.

Includes bibliographical references and index.

1. Hypotheses Testing for Two Samples
1.1Sign Test for Location Parameter for Matched Paired Samples
1.2 Wilcoxon Signed-Rank Test for Location Parameter for Matched Paired Samples
1.3Wilcoxon Rank-Sum Test for Location Parameter for Two Independent Samples
1.4 Ansari-Bradley Test for Scale Parameter for Two Independent Samples
1.5 Kolmogorov-Smirnov Test for Equality of Distributions
2. Hypotheses Testing for Several Samples
2.1 Friedman Rank Test for Location Parameter for Several Dependent Samples
2.2 Kruskal-Wallis H-Test for Location Parameter for Several Independent Samples
3. Tests for Categorical Data
3.1 Spearman Rank Correlation Coefficient Test
3.2 Fisher Exact Test
4. Nonparametric Regression
4.1 Loess Regression
4.2 Thin-Plate Smoothing Spline Method
5. Nonparametric Generalized Additive Regression
5.1 Definition
5.2 Nonparametric Binary Logistic Model
5.3 Nonparametric Poisson Model
6. Time-to-Event Analysis
6.1 Kaplan-Meier Estimator of Survival Function
6.2 Log-Rank Test for Comparison of Two Survival Functions
6.3 Cox Proportional Hazards Model
7. Univariate Probability Density Estimation
7.1 Histogram
7.2 Kernel Density Estimator
8. Resampling Methods for Interval Estimation
8.1 Jackknife
8.2 Bootstrap
Appendix A: Tables
Appendix B: Answers to Exercises
Recommended Books
Index of Notation
Index Exercises appear at the end of each chapter.

"Preface This book has been written as a textbook for the second-year graduate course taught by the author in the Master's program in Applied Statistics at California State University, Long Beach. The goal of this course is to teach applications of nonparametric methods in statistics, starting with the hypotheses testing and moving on to regression, time-to-event analysis, density estimation and resampling methods. Being a textbook, this book is abundant with examples and exercises. The settings were taken from various scientific disciplines: health sciences, psychology, social sciences, education, clinical trials, to name a few. The settings and properly disguised data came from consulting projects that the author had been involved in over the past decade. All examples and exercises require the use of SAS 9.3 software. In the text, complete SAS codes are given for all examples. To prevent typing errors, the data sets for exercises are available on the book website. Instructors' solutions manual for all exercises is available to instructors upon request on the same website. Olga Korosteleva March, 2013"--