Applied Nonparametric Statistical Methods, Third Edition: (Chapman & Hall/CRC Texts in Statistical Science)

This new edition follows the basic easy-to-digest pattern that was so well received by users of the earlier editions. The authors substantially update and expand Applied Nonparametric Statistical Methods to reflect changing attitudes towards applied statistics, new developments, and the impact of more widely available and better statistical software.The book takes into account computing developments since the publication of the popular Second Edition, rearranging the material in a more logical order, and introducing new topics. It emphasizes better use of significance tests and focuses greater attention on medical and dental applications. Applied Nonparametric Statistical Methods: Third Edition explains the rationale of procedures with a minimum of mathematical detail, making it not only an outstanding textbook, but also an up-to-date reference for professionals who do their own statistical analyses.N ew in the Third Edition:oExpanded coverage of topics - such as ethical considerations and calculation of power and of sample sizes neededoRefers to a wide variety of statistical packages - such as StatXact, Minitab, Testimate, S-plus, Stata, and SPSSoIncludes sections on the analysis of angular data, the use of capture-recapture methods, the measurement of agreement between observers, runs tests, and regression diagnostics.

Table of Contents:
PREFACE INTRODUCING NONPARAMETRIC METHODS Basic Statistics Samples and Populations Hypothesis Tests Estimation Ethical Issues Computers and Nonparametric Methods Further Reading CENTRALITY INFERENCE FOR SINGLE SAMPLES Using Measurement Data Inferences about Medians Based on Ranks The Sign Test Transformation of Ranks Asymptotic Results Robustness OTHER SINGLE-SAMPLE INFERENCE Inferences for Dichotomous Data Tests Related to the Sign Test Matching Samples to Distributions Angular Data A Runs Test for Randomness METHODS FOR PAIRED SAMPLES Comparisons in Pairs A Less Obvious Use of the Sign Test Power and Sample Size METHODS FOR TWO INDEPENDENT SAMPLES Centrality Tests and Estimates Rank Based Tests The Median Test Normal Scores Tests for Survival Data Asymptotic Approximation Power and Sample Size Tests for Equality of Variance Tests for a Common Distribution THREE OR MORE SAMPLES Comparisons with Parametric Methods Centrality Tests for Independent Samples Centrality Tests for Related Samples More Detailed Treatment Comparisons Tests for Heterogeneity of Variance Some Miscellaneous Considerations CORRELATION AND CONCORDANCE Correlation and Bivariate Data Ranked Data for Several Variables Agreement REGRESSION Bivariate Linear Regression Multiple Regression Nonparametric Regression Models Other Multivariate Data Problems CATEGORICAL DATA Categories and Counts Nominal Attribute Categories Ordered Categorical Data Goodness-of-Fit Tests for Discrete Data Extension of McNemar's Test ASSOCIATION IN CATEGORICAL DATA The Analysis of Association Some Models for Contingency Tables Combining and Partitioning of Tables Power ROBUST ESTIMATION When Assumptions Break Down Outliers and Influence The Bootstrap M-Estimators and Other Robust Estimators APPENDIX REFERENCES SO

Review :
"Strengths of this text certainly include its organization and writing style. Applied Nonparametric Statistical Methods provides a very clear exposition of modern nonparametric methods. Many students and practitioners will find it an excellent resource and reference for nonparametric statistics." -Technometrics, 2003" extremely valuable for statisticians as well as for researchers in applied fields. This well-written book is highly recommended for those readers who want to get a feeling for the nonparametric methods which they apply when analysing their data." - Statistics in Medicine, 2004 About the Second Edition "Nicely laid out for practitioners with minimal theory, very deliberate explanations, and lots of illustrations." -Technometrics "This is the third edition of a very good book on nonparametric statisticsgoes far beyond being a compendium of useful methods. It aims at promoting understanding as well. Good statistical practice is exemplified throughout Particularly commendable are their discussions of multiple comparisons and conditioning in the two by two contingency table If I could only have one book on nonparametric methods, this would be my choice. It is highly recommended." -Short Book Reviews of the ISI, Vol. 21, No. 2, August, 2001