Selective inference in complex research

Philos Trans A Math Phys Eng Sci. 2009 Nov 13;367(1906):4255-71. doi: 10.1098/rsta.2009.0127.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical*
  • Diabetes Mellitus, Type 2 / genetics
  • Genomics
  • Reproducibility of Results
  • Research Design*
  • Risk