Correlation and Large-Scale Simultaneous Significance Testing

By Bradley Efron. 2007

450 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0c2a04d474ccfef4085235b60d00524994cd33bc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

BMC Bioinformatics (2005, unknown): “The variance of pairwise correlations was previously described as an important parameter in FDR estimation [20].”
Large Covariance Estimation by Thresholding Principal Orthogonal Complements (2011, unknown): “Our theory (Theorem 3.3) gives a formal justification to the framework of Efron (2007, 2010).”
A Selective Overview of Variable Selection in High Dimensional Feature Space (2009, methodology): “…signiﬁcant genes between the treatment and control groups (Dudoit, Shaﬀer and Boldrick (2003); Storey and Tibshirani (2003); Fan and Ren (2006); Efron (2007)), feature ranking using a generalized correlation (Hall and Miller (2009a)), non-parametric learning under sparse additive models…”
Robustness of multiple testing procedures against dependence (2009, background): “Efron (2007) has suggested correlation corrections for large-scale simultaneous hypothesis testing.”
A Factor Model Approach to Multiple Testing Under Dependence (2009, methodology): “For example, a hierarchically structured correlation is proposed by Efron (2007) to explain the discrepancy of the p-values’ distribution relative to the expected distribution under assumption of independence. Different types of dependence deduced from specific considerations on the coexpressions of”
Large‐scale multiple testing under dependence (2009, methodology): “The effects of correlation on FDR procedures have been discussed by Benjamini and Yekutieli (2001), Finner and Roters (2002), Owen (2005), Sarkar (2006) and Efron (2007), among others. Efron (2007) noted that correlation may result in overly liberal or overly conservative testing procedures and so m”
Large-scale inference (2010, methodology): “Most of this chapter’s material comes from Efron (2009a), where tests for column-wise independence are investigated more thoroughly, and Efron (2007a).”
False discovery rates: a new deal (2016, methodology): “These two issues are connected: specifically, unmeasured confounding factors can cause both correlations among tests and deviations from the theoretical null (Efron, 2007; Leek and Storey, 2007).”
Statistical Applications in Genetics and Molecular Biology A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics (2011, unknown): “However, we now suggest to employ the local fdr, as this fits more naturally with the mixture model setup, and because it takes account of the dependencies among the estimated partial correlation coefficients (Efron, 2005a).”
Pointwise testing with functional data using the Westfall–Young randomization method (2008, methodology): “Furthermore, we could not find a method comparable to that of Westfall and Young which applies to functional data controlling for the false discovery rate, although the methods presented in Efron (2007) may prove useful for solving this problem.”
Size, power and false discovery rates (2007, background): “The theoretical or permutation null yields seriously misleading results for the HIV data, as discussed in [10].”
Asymptotic optimality of the Westfall--Young permutation procedure for multiple testing under dependence (2011, background): “Another viewpoint is given by Efron [10], who proposed a novel empirical choice of an appropriate null distribution for large-scale significance testing.”