title: Clinical versus mechanical prediction: a meta-analysis.
abstract: The process of making judgments and decisions requires a method for combining data. To compare the accuracy of clinical and mechanical (formal, statistical) data-combination techniques, we performed a meta-analysis on studies of human health and behavior. On average, mechanical-prediction techniques were about 10% more accurate than clinical predictions. Depending on the specific analysis, mechanical prediction substantially outperformed clinical prediction in 33%-47% of studies examined. Although clinical predictions were often as accurate as mechanical predictions, in only a few studies (6%-16%) were they substantially more accurate. Superiority for mechanical-prediction techniques was consistent, regardless of the judgment task, type of judges, judges' amounts of experience, or the types of data being combined. Clinical predictions performed relatively less well when predictors included clinical interview data. These data indicate that mechanical predictions of human behaviors are equal or superior to clinical prediction methods for a wide range of circumstances.
authors.affiliation: Department of Psychology, University of Minnesota, Minneapolis 55455-0344, USA. william.m.grove-1@tc.umn.edu
authors.forename: W M
authors.initials: WM
authors.lastname: Grove
authors.forename: D H
authors.initials: DH
authors.lastname: Zald
authors.forename: B S
authors.initials: BS
authors.lastname: Lebow
authors.forename: B E
authors.initials: BE
authors.lastname: Snitz
authors.forename: C
authors.initials: C
authors.lastname: Nelson
mesh_terms: D003658:Decision Making, Computer-Assisted; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data*; D006801:Humans; D008432:Mathematical Computing; D015203:Reproducibility of Results