Resampling-Based Multiple Testing

Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power. Resampling-Based Adjustments: Basic Concepts.

Continuous Data Applications: Univariate Analysis.

Continuous Data Applications: Multivariate Analysis.

Binary Data Applications.

Further Topics.

Practical Applications.

Appendices.

References.

List of Algorithms.

List of Examples.

Indexes.

Peter H. Westfall and S. Stanley Young are the authors of Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment, published by Wiley.