Selective inference in complex research
Yoav Benjamini, Ruth Heller, Daniel Yekutieli
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Source: Crossref
Published: Nov 13, 2009
DOI: 10.1098/rsta.2009.0127
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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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