On the Screening of Large Numbers of Significance Tests

Abstract

A brief review is given of procedures for the collective analysis of a large number of significance tests. A simple procedure previously supplied for isolating ‘real’ effects on the basis of a large number of significance tests is generalized to deal with two-sided tests and is also related more explicitly to the false discovery rate.

Keywords:

• False discovery rate
• mixture of distributions
• Bayes factor
• multiple testing

Acknowledgements

This work has been supported by a UICC International Cancer Technology Transfer Fellowship.