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Selective inference in complex research

Yoav Benjamini, Ruth Heller, Daniel Yekutieli

Source record

Source: Crossref

Published: Nov 13, 2009

DOI: 10.1098/rsta.2009.0127

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Source abstract

We explain the problem of selective inference in complex research using a recently published study: a replicability study of the associations in order to reveal and establish risk loci for type 2 diabetes. The false discovery rate approach to such problems will be reviewed, and we further address two problems: (i) setting confidence intervals on the size of the risk at the selected locations and (ii) selecting the replicable results.

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