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| Research article summary (published 30 Jul 2003): |
Understanding and using the implicit association test: I. An improved scoring algorithm.
Full Abstract
In reporting Implicit Association Test (IAT) results, researchers have most often used scoring conventions described in the first publication of the IAT (A.G. Greenwald, D.E. McGhee, & J.L.K. Schwartz, 1998). Demonstration IATs available on the Internet have produced large data sets that were used in the current article to evaluate alternative scoring procedures. Candidate new algorithms were examined in terms of their (a) correlations with parallel self-report measures, (b) resistance to an artifact associated with speed of responding, (c) internal consistency, (d) sensitivity to known influences on IAT measures, and (e) resistance to known procedural influences. The best-performing measure incorporates data from the IAT's practice trials, uses a metric that is calibrated by each respondent's latency variability, and includes a latency penalty for errors. This new algorithm strongly outperforms the earlier (conventional) procedure.
Author information
Author/s: Greenwald, Anthony G (AG); Nosek, Brian A (BA); Banaji, Mahzarin R (MR);
Affiliation: Department of Psychology, University of Washington, Seattle 98195-1525, USA. agg(-atsign-)u.washington.edu
Grants: MH-01533 (Agency:NIMH NIH HHS) ; MH-41328 (Agency:NIMH NIH HHS) ; MH-57672 (Agency:NIMH NIH HHS)
Journal and publication information
Publication Type: Journal Article; Research Support, U.S. Gov't, P.H.S.
Journal: Journal of personality and social psychology (J Pers Soc Psychol), published in United States. (Language: eng)
Reference: 2003-Aug; vol 85 (issue 2) : pp 197-216
Dates: Created 2003/08/14; Completed 2004/02/19; Revised 2009/11/11;
PMID: 12916565, status: MEDLINE (last retrieval date: 11/11/2009, IMS Date: )
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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