A simple procedure for the selection of significant effects

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Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.

Keywords: Bayes factor; Discrimination; Empirical Bayes; False discovery rate; Mixture of distributions; Multiple testing

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1369-7412.2004.05695.x

Affiliations: 1: Nuffield College, Oxford, UK. 2: Hong Kong University of Science and Technology, People's Republic of China

Publication date: April 1, 2004

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