Nonparametric statistical tests : a computational approach
 Author/Creator
 Neuhäuser, Markus.
 Language
 English.
 Imprint
 Boca Raton, FL : CRC Press, c2012.
 Physical description
 xvii, 229 p. : ill. ; 25 cm.
Access
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 203226) and index.
 Contents

 Introduction and Overview Nonparametric tests for the location problem Tests in case of heteroscedasticity Tests for the general alternative Ordered categorical and discrete data The conservativeness of permutation tests Further examples for the comparison of two groups Onesample tests and tests for paired data Tests for more than two groups Independence and correlation Stratified studies and combination of pvalues Estimation and confidence intervals Appendix. Nonparametric tests in R References.
 (source: Nielsen Book Data)
 Publisher's Summary
 Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and littleknown methods such as the BaumgartnerWeissSchindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous reallife data from various areas, including the bible, and their analyses provide for greatly diversified reading. The book covers: * Nonparametric twosample tests for the locationshift model, specifically the FisherPitman permutation test, the Wilcoxon rank sum test, and the BaumgartnerWeissSchindler test * Permutation tests, locationscale tests, tests for the nonparametric BehrensFisher problem, and tests for a difference in variability * Tests for the general alternative, including the (Kolmogorov)Smirnov test, ordered categorical, and discrete numerical data * Wellknown onesample tests such as the sign test and Wilcoxon's signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a onesample bootstrap test are presented. * Tests for more than two groups, the following tests are described in detail: the KruskalWallis test, the permutation F test, the JonckheereTerpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groups * The concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests * The applicability of computerintensive methods such as bootstrap and permutation tests for nonstandard situations and complex designs Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap.
(source: Nielsen Book Data)
Subjects
 Subject
 Nonparametric statistics.
Bibliographic information
 Publication date
 2012
 Responsibility
 Markus Neuhäuser.
 ISBN
 9781439867037
 1439867038