What is it about?

This paper applies methods of estimating the local false discovery rate to one or more hypothesis tests.

Featured Image

Why is it important?

In testing many hypotheses, the importance of local discovery rates is that they strike a balance between the excessive false negatives of adjusted p values and the excessive false positives of non-local false discovery rates. This paper explores the possibility that the advantages of the local false discovery rate also apply to the case of very few hypotheses or even to one hypothesis.

Perspectives

This is a first step toward modifying estimators of the local false discovery rate for the very smallest numbers of hypothesis tests.

David R. Bickel
University of North Carolina at Greensboro

Read the Original

This page is a summary of: Small-scale Inference: Empirical Bayes and Confidence Methods for as Few as a Single Comparison, International Statistical Review, August 2014, Wiley,
DOI: 10.1111/insr.12064.
You can read the full text:

Read

Resources

Contributors

The following have contributed to this page