Nonparametric methods in statistics with SAS applications / Olga Korosteleva
- Author:
- Korosteleva, Olga
- Published:
- Boca Raton : CRC Press, [2014]
- Physical Description:
- vi, 183 pages : illustrations ; 24 cm.
- Series:
- Contents:
- Machine generated contents note: 1.Hypotheses Testing for Two Samples -- 1.1.Sign Test for Location Parameter for Matched Paired Samples -- 1.1.1.Testing Procedure -- 1.1.2.SAS Implementation -- 1.1.3.Examples -- 1.2.Wilcoxon Signed-Rank Test for Location Parameter for Matched Paired Samples -- 1.2.1.Testing Procedure -- 1.2.2.Calculation of Critical Values: Example -- 1.2.3.SAS Implementation -- 1.2.4.Examples -- 1.3.Wilcoxon Rank-Sum Test for Location Parameter for Two Independent Samples -- 1.3.1.Test Procedure -- 1.3.2.Calculation of Critical Values: Example -- 1.3.3.SAS Implementation -- 1.3.4.Examples -- 1.4.Ansari-Bradley Test for Scale Parameter for Two Independent Samples -- 1.4.1.Test Procedure -- 1.4.2.Calculation of Critical Values: Examples -- 1.4.3.SAS Implementation -- 1.4.4.Examples -- 1.5.Kolmogorov-Smirnov Test for Equality of Distributions -- 1.5.1.Testing Procedure -- 1.5.2.Calculation of Critical Values: Example -- 1.5.3.SAS Implementation -- 1.5.4.Examples -- Exercises -- 2.Hypotheses Testing for Several Samples -- 2.1.Friedman Rank Test for Location Parameter for Several Dependent Samples -- 2.1.1.Testing Procedure -- 2.1.2.SAS Implementation -- 2.1.3.Examples -- 2.2.Kruskal-Wallis H-Test for Location Parameter for Several Independent Samples -- 2.2.1.Testing Procedure -- 2.2.2.SAS Implementation -- 2.2.3.Examples -- Exercises -- 3.Tests for Categorical Data -- 3.1.Spearman Rank Correlation Coefficient Test -- 3.1.1.Computation of Spearman Correlation Coefficient -- 3.1.2.Testing Procedure -- 3.1.3.Calculation of Critical Values: Example -- 3.1.4.SAS Implementation -- 3.1.5.Examples -- 3.2.Fisher Exact Test -- 3.2.1.Testing Procedure -- 3.2.2.Calculation of P-values: Example -- 3.2.3.SAS Implementation -- 3.2.4.Examples -- Exercises -- 4.Nonparametric Regression -- 4.1.Loess Regression -- 4.1.1.Definition -- 4.1.2.Smoothing Parameter Selection Criterion -- 4.1.3.SAS Implementation: Fitting Loess Regression -- 4.1.4.SAS Implementation: Plotting Fitted Loess Curve -- 4.1.5.SAS Implementation: Plotting 3D Scatterplot -- 4.1.6.SAS Implementation: Plotting Fitted Loess Surface -- 4.1.7.Examples -- 4.2.Thin-Plate Smoothing Spline Method -- 4.2.1.Definition -- 4.2.2.SAS Implementation: Fitting Spline -- 4.2.3.SAS Implementation: Plotting Fitted Spline Curve -- 4.2.4.SAS Implementation: Plotting Fitted Spline Surface -- 4.2.5.Examples -- Exercises -- 5.Nonparametric Generalized Additive Regression -- 5.1.Definition -- 5.2.Nonparametric Binary Logistic Model -- 5.2.1.Definition -- 5.2.2.SAS Implementation -- 5.2.3.Examples -- 5.3.Nonparametric Poisson Model -- 5.3.1.Definition -- 5.3.2.SAS Implementation -- 5.3.3.Examples -- Exercises -- 6.Time-to-Event Analysis -- 6.1.Kaplan-Meier Estimator of Survival Function -- 6.1.1.Derivation of KM Estimator -- 6.1.2.SAS Implementation -- 6.1.3.Example -- 6.2.Log-Rank Test for Comparison of Two Survival Functions -- 6.2.1.Testing Procedure -- 6.2.2.SAS Implementation -- 6.2.3.Example -- 6.3.Cox Proportional Hazards Model -- 6.3.1.Two Alternative Definitions of Cox Model -- 6.3.2.Estimation of Regression Coefficients and Baseline Survival Function -- 6.3.3.Interpretation of Regression Coefficients -- 6.3.4.SAS Implementation -- 6.3.5.Example -- Exercises -- 7.Univariate Probability Density Estimation -- 7.1.Histogram -- 7.1.1.Definition -- 7.1.2.SAS Implementation -- 7.1.3.Example -- 7.2.Kernel Density Estimator -- 7.2.1.Definition -- 7.2.2.SAS Implementation -- 7.2.3.Example -- Exercises -- 8.Resampling Methods for Interval Estimation -- 8.1.Jackknife -- 8.1.1.Estimation Procedure -- 8.1.2.SAS Implementation -- 8.1.3.Examples -- 8.2.Bootstrap -- 8.2.1.Estimation Procedure -- 8.2.2.SAS Implementation -- 8.2.3.Examples.
- Summary:
- "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"--
- Subject(s):
- ISBN:
- 9781466580626 (pbk.)
1466580623 (pbk.) - Bibliography Note:
- Includes bibliographical references and index.
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