Handbook of Multiple Comparisons

Multiple comparisons

While multiple testing procedures have been the focus of much statistical research, an important facet of the problem is how to deal with possible confounding. Procedures have been developed by authors in genetics and statistics. In this chapter, we relate these proposals. We propose two new multiple testing approaches within this framework. The first combines sensitivity analysis methods with ...

Multiple comparisons, explained.

The commentary by Savitz and Olshan (1) and the response by Thompson (2) form a fascinating contrast. Savitz and Olshan speak in the language of epidemiology, complaining about the seeming arbitrary and antiscientific dictates of conventional (frequentist) statistical methodology, particularly as it applies to the study of many associations. Thompson, speaking mainly in the language of statisti...

Multiple comparisons procedures.

In biomedical research, a common question posed by investigators is whether or not an outcome of interest differs significantly between multiple independent groups of subjects in the study sample. For example, in a randomized clinical trial focusing on differences in a parameter of cardiovascular health such as systolic blood pressure or heart rate that is measured on a continuum, one might mak...

Statistical Comparisons of Multiple Classifiers

Multiple comparisons: philosophies and illustrations.

Statistical procedures underpin the process of scientific discovery. As researchers, one way we use these procedures is to test the validity of a null hypothesis. Often, we test the validity of more than one null hypothesis. If we fail to use an appropriate procedure to account for this multiplicity, then we are more likely to reach a wrong scientific conclusion-we are more likely to make a mis...