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SAS Companion for Nonparametric Statistics

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ISBN-10: 0534422209

ISBN-13: 9780534422202

Edition: 2006

Authors: Scott J. Richter, James J. Higgins

List price: $199.95
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Need a guide to using SAS to carry out non-parametric analysis? SAS COMPANION FOR NONPARAMETRIC STATISTICS provides an excellent knowlege base and provides examples you can use to practice using the program. All SAS examples presented are self-contained and can be entered into SAS as they appear, and executed. Thus, you don't have to deal with issues of creating SAS data sets before using the programs. In addition to presenting the SAS code to obtain various nonparametric analyses, brief introductions to the methods themselves are provided. Particular attention is given to how SAS calculates the results it presents.
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Book details

List price: $199.95
Copyright year: 2006
Publisher: Brooks/Cole
Publication date: 6/1/2005
Binding: Paperback
Pages: 128
Size: 7.50" wide x 9.00" long x 0.50" tall
Weight: 0.440

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.

One-Sample Methods
Binomial Test for the Median
A Confidence Interval for the Pth Quantile
Two-Sample Methods
A Two-Sample Permutation Test
Random Sampling the Permutations
The Wilcoxon Tank-Sum Test
Other Scoring Systems
Tests for Equality of Scale Parameters and Omnibus Tests
Nonparametric Bootstrap Methods for Two Samples
K-Sample Methods
K-Sample Permutation Tests
The Kruskal-Wallis Test
Multiple Comparisons
Ordered Alternatives
Paired Comparisons and Blocked Designs
Paired Comparisons
Friedman's Test for Randomized Complete Block Design
Tests of Association for Bivariate Data
Measures of Association for Bivariate Data
Summary of Options for Obtaining P-values for Measures of Association
Tests of Association for Contingency Tables
Measures of Association for Contingency Tables
Chi-Square and Permutation Tests for Contingency Tables
Fisher's Exact Test for a 2X2 Contingency Table
Contingency Tables with Ordered Categories
Tables with Multiple Strata
McNemar's Test
Analysis of Censored Data
Estimating The Survival Function
Permutation Test for Type I and Type II Censored Data
Permutation Tests for Randomly Censored Data
Comparing Survival Functions
Multivariate Permutation Tests
Tests Based on Raw Data
Tests Based on Ranks
Smoothing Methods and Robust Model Fitting
Estimating the Probability Density Function
Nonparametric Curve Smoothing
Robust Regression