title: Statistical analysis of the National Institutes of Health peer review system.
abstract: A statistical model is proposed for the analysis of peer-review ratings of R01 grant applications submitted to the National Institutes of Health. Innovations of this model include parameters that reflect differences in reviewer scoring patterns, a mechanism to account for the transfer of information from an application's preliminary ratings and group discussion to final ratings provided by all panel members and posterior estimates of the uncertainty associated with proposal ratings. Application of this model to recent R01 rating data suggests that statistical adjustments to panel rating data would lead to a 25% change in the pool of funded proposals. Viewed more broadly, the methodology proposed in this article provides a general framework for the analysis of data collected interactively from expert panels through the use of the Delphi method and related procedures.
authors.affiliation: University of Texas M.D. Anderson Cancer Center, 1400 Pressler Street, Unit #1411, Houston, TX 77030, USA. vejohnson@mdanderson.org
authors.forename: Valen E
authors.initials: VE
authors.lastname: Johnson
mesh_terms: D035843:Biomedical Research / Q000191:economics; D007256:Information Systems / Q000191:economics; D015233:Models, Statistical; D009316:National Institutes of Health (U.S.) / Q000191:economics; D017712:Peer Review, Research / Q000379:methods; D014481:United States