title: Implicit measures: A normative analysis and review.
abstract: Implicit measures can be defined as outcomes of measurement procedures that are caused in an automatic manner by psychological attributes. To establish that a measurement outcome is an implicit measure, one should examine (a) whether the outcome is causally produced by the psychological attribute it was designed to measure, (b) the nature of the processes by which the attribute causes the outcome, and (c) whether these processes operate automatically. This normative analysis provides a heuristic framework for organizing past and future research on implicit measures. The authors illustrate the heuristic function of their framework by using it to review past research on the 2 implicit measures that are currently most popular: effects in implicit association tests and affective priming tasks. (PsycINFO Database Record (c) 2009 APA, all rights reserved).
authors.affiliation: Department of Psychology, Ghent University.
authors.forename: Jan
authors.initials: J
authors.lastname: De Houwer
authors.affiliation: Department of Psychology, University of Freiburg.
authors.forename: Sarah
authors.initials: S
authors.lastname: Teige-Mocigemba
authors.affiliation: Department of Psychology, Ghent University.
authors.forename: Adriaan
authors.initials: A
authors.lastname: Spruyt
authors.affiliation: Department of Psychology, Ghent University.
authors.forename: Agnes
authors.identifier: 0000-0002-5137-557X
authors.initials: A
authors.lastname: Moors
mesh_terms: D000339:Affect / Q000502:physiology*; D001244:Association; D001290:Attitude; D003463:Cues; D006801:Humans; D007389:Internal-External Control; D008568:Memory / Q000502:physiology; D010556:Personality Tests / Q000592:standards*; D012016:Reference Values; D013240:Stereotyping; D013647:Task Performance and Analysis