1st Edition
by Thomas W. O'Gorman (Author)
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.
