Selective inference in complex research

Yoav Benjamini*, Ruth Heller, Daniel Yekutieli

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

98 Scopus citations


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. This journal is

Original languageEnglish
Pages (from-to)4255-4271
Number of pages17
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Issue number1906
StatePublished - 13 Nov 2009


  • False coverage rate
  • False discovery rate
  • Genome-wise association scan
  • Multiple comparisons
  • Replicability


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