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Assessing mean and median filters in multiple testing for large-scale imaging data

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  • Chunming Zhang

Abstract

A new multiple testing procedure, called the FDR L procedure, was proposed by Zhang et al. (Ann Stat 39:613–642, 2011 ) for detecting the presence of spatial signals for large-scale 2D and 3D imaging data. In contrast to the conventional multiple testing procedure, the FDR L procedure substitutes each p-value by a locally aggregated median filter of p-values. This paper examines the performance of another commonly used filter, mean filter, in the FDR L procedure. It is demonstrated that when the p-values are independent and uniformly distributed under the true null hypotheses, (i) in view of estimating the resulting false discovery rate, the mean filter better alleviates the “lack of identification phenomenon” of the FDR L procedure than the median filter; (ii) in view of signal detection, the median filter enjoys the “edge-preserving property” and lends support to its better performance in detecting sparse signals than the mean filter. Copyright Sociedad de Estadística e Investigación Operativa 2014

Suggested Citation

  • Chunming Zhang, 2014. "Assessing mean and median filters in multiple testing for large-scale imaging data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 51-71, March.
    • Handle: RePEc:spr:testjl:v:23:y:2014:i:1:p:51-71
    DOI: 10.1007/s11749-013-0341-7
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    1. S. Sadooghi-Alvandi & A. Nematollahi & R. Habibi, 2009. "On the distribution of the sum of independent uniform random variables," Statistical Papers, Springer, vol. 50(1), pages 171-175, January.
    2. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205, February.
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