A nonparametric empirical Bayes framework for large-scale multiple testing

R. Martin, S. t. Tokdar
2011 Biostatistics  
We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-null cases. We use a computationally efficient predictive recursion marginal likelihood procedure to estimate the model parameters, even the nonparametric mixing distribution. This leads to a nonparametric empirical Bayes testing procedure, which we call PRtest, based on thresholding the estimated
more » ... cal false discovery rates. Simulations and real-data examples demonstrate that, compared to existing approaches, PRtest's careful handling of the non-null density can give a much better fit in the tails of the mixture distribution which, in turn, can lead to more realistic conclusions.
doi:10.1093/biostatistics/kxr039 pmid:22085895 fatcat:4kwuf4f6vzgs7o3zjzc2ldfuke