title: Selective inference in complex research.
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.
authors.affiliation: Department of Statistics and Operations Research, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel. ybenja@tau.ac.il
authors.forename: Yoav
authors.initials: Y
authors.lastname: Benjamini
authors.forename: Ruth
authors.initials: R
authors.lastname: Heller
authors.forename: Daniel
authors.initials: D
authors.lastname: Yekutieli
mesh_terms: D003627:Data Interpretation, Statistical; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D023281:Genomics; D015203:Reproducibility of Results; D012107:Research Design; D012306:Risk