Adaptive Tests of Significance Using Permutations of Residuals with R and SAS

Provides 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 estimates

Throughout 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.

Table of Contents

1 Introduction 1
2 Smoothing Methods and Normalizing Transformations 15
3 A Two-Sample Adaptive Test 43
4 Permutation Tests with Linear Models 75
5 An Adaptive Test for a Subset of Coefficients 87
6 More Applications of Adaptive Tests 111
7 The Adaptive Analysis of Paired Data 149
8 Multicenter and Cross-Over Trials 169
9 Adaptive Multivariate Tests 191
10 Analysis of Repeated Measures Data 207
11 Rank-Based Tests of Significance 235
12 Adaptive Confidence Intervals and Estimates 253

Appendix A: R Code for Univariate Adaptive Tests 283
Appendix B: SAS Macro for Adaptive Tests 287
Appendix C: SAS Macro for Multiple Comparisons Procedures 299
Appendix D: R Code for Adaptive Tests with Blocking Factors 303
Appendix E: R Code for Adaptive Test with Paired Data 305
Appendix F: SAS Macro for Adaptive Test with Paired Data 309
Appendix G: R Code for Multivariate Adaptive Tests 313
Appendix H: R Code for Confidence Intervals and Estimates 317
Appendix I: SAS Macro for Confidence Intervals 321
Appendix J: SAS Macro for Estimates 329