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• W2017002453 abstract "The objective of this paper is to quantify the effect of correlation in false discovery rate analysis. Specifically, we derive approximations for the mean, variance, distribution and quantiles of the standard false discovery rate estimator for arbitrarily correlated data. This is achieved using a negative binomial model for the number of false discoveries, where the parameters are found empirically from the data. We show that correlation may increase the bias and variance of the estimator substantially with respect to the independent case, and that in some cases, such as an exchangeable correlation structure, the estimator fails to be consistent as the number of tests becomes large." @default.
• W2017002453 created "2016-06-24" @default.
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• W2017002453 date "2011-02-25" @default.
• W2017002453 modified "2023-09-30" @default.
• W2017002453 title "The effect of correlation in false discovery rate estimation" @default.
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• W2017002453 doi "https://doi.org/10.1093/biomet/asq075" @default.
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