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2020 | OriginalPaper | Buchkapitel

Correlation Between the True and False Discoveries in a Positively Dependent Multiple Comparison Problem

verfasst von : Xing Qiu, Rui Hu

Erschienen in: Statistical Modeling for Biological Systems

Verlag: Springer International Publishing

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Abstract

Testing multiple hypotheses when observations are positively correlated is very common in practice. The dependence between observations can induce dependence between test statistics and distort the joint distribution of the true and false positives. It has a profound impact on the performance of common multiple testing procedures. While the marginal statistical properties of the true and false discoveries such as their means and variances have been extensively studied in the past, their correlation remains unknown.

By conducting a thorough simulation study, we find that the true and false positives are likely to be negatively correlated if testing power is high and the opposite holds true—they are likely to be positively correlated if testing power is low. The fact that positive dependence between observations can induce negative correlation between the true and false discoveries may assist researchers in designing multiple testing procedures for dependent tests in the future.

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Vorheriges Kapitel A Study of the Correlation Structure of Microarray Gene Expression Data Based on Mechanistic Modeling of Cell Population Kinetics

Nächstes Kapitel Multiple Testing Procedures: Monotonicity and Some of Its Implications

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In order to achieve a better formatting effect, Table 4 only includes simulation results with ρ = 0.0 and 0.4. Table 5 shows the results with ρ = 0.8.

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Titel: Correlation Between the True and False Discoveries in a Positively Dependent Multiple Comparison Problem
verfasst von: Xing Qiu
Rui Hu
Verlag: Springer International Publishing
Buch: Statistical Modeling for Biological Systems
Print ISBN: 978-3-030-34674-4

Electronic ISBN: 978-3-030-34675-1

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-34675-1_4

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