O'Gorman T.W. Adaptive Tests of Significance Using Permutations of Residuals with R and SAS

Wiley, 2012. — 347 p. — ISBN: 0470922257, 9780470922255Provides the tools needed to successfully perform adaptive tests across a broad range of datasets.
Adaptive Tests of Significance Using Permutations of Residuals with R and SAS illustrates the power of adaptive tests and showcases their ability to adjust the testing method to suit a particular set of data. The book utilizes state-of-the-art software to demonstrate the practicality and benefits for data analysis in various fields of study.
Beginning with an introduction, the book moves on to explore the underlying concepts of adaptive tests, including:
Smoothing methods and normalizing transformations
Permutation tests with linear methods
Applications of adaptive tests
Multicenter and cross-over trials
Analysis of repeated measures data
Adaptive confidence intervals and estimatesThroughout the book, numerous figures illustrate the key differences among traditional tests, nonparametric tests, and adaptive tests. R and SAS software packages are used to perform the discussed techniques, and the accompanying datasets are available on the book's related website. In addition, exercises at the end of most chapters enable readers to analyze the presented datasets by putting new concepts into practice.
Adaptive Tests of Significance Using Permutations of Residuals with R and SAS is an insightful reference for professionals and researchers working with statistical methods across a variety of fields including the biosciences, pharmacology, and business. The book also serves as a valuable supplement for courses on regression analysis and adaptive analysis at the upper-undergraduate and graduate levels.Smoothing Methods and Normalizing Transformations
A Two-Sample Adaptive Test
Permutation Tests with Linear Models
An Adaptive Test for a Subset of Coefficients
More Applications of Adaptive Tests
The Adaptive Analysis of Paired Data
Multicenter and Cross-Over Trials
Adaptive Multivariate Tests
Analysis of Repeated Measures Data
Rank-Based Tests of Significance
Adaptive Confidence Intervals and Estimates
Appendix A: R Code for Univariate Adaptive Tests
Appendix B: SAS Macro for Adaptive Tests
Appendix C: SAS Macro for Multiple Comparisons Procedures
Appendix D: R Code for Adaptive Tests with Blocking Factors
Appendix E: R Code for Adaptive Test with Paired Data
Appendix F: SAS Macro for Adaptive Test with Paired Data
Appendix G: R Code for Multivariate Adaptive Tests
Appendix H: R Code for Confidence Intervals and Estimates
Appendix I: SAS Macro for Confidence Intervals
Appendix J: SAS Macro for Estimates