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The individual-level precision of implicit measures

Abstract:
Implicit measures are used extensively in psychological science. One fundamental goal of these measures is to provide information diagnostic of an individual’s attitudes or beliefs. After 25 years of research, this goal has not been achieved. We argue that this is because psychologists have not yet even quantified the individual-level precision of implicit measures, much less calibrated them to it. In this paper, we examine the individual-level precision of six different implicit measures across three different attitude domains (race, politics, and self-esteem) using a very large open dataset. Despite some variation, we find that there is substantial room for improvement for the precision of implicit measures as measures of individual attitudes. We recommend that researchers who wish to make theoretical inferences about individuals directly quantify individual-level precision to calibrate their tasks appropriately, both in the context of implicit measures and with tasks in psychological science more broadly.
Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Role:
Author


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Funder identifier:
https://ror.org/02k7v4d05


Publisher:
Springer
Journal:
Behavior Research Methods More from this journal
Volume:
58
Issue:
1
Article number:
21
Publication date:
2025-12-08
Acceptance date:
2025-10-14
DOI:
EISSN:
1554-3528
ISSN:
1554351X, 1554-351X


Language:
English
Keywords:
Pubs id:
2350431
UUID:
uuid_3ecb2356-c368-4b58-ba89-a4883f7abea5
Local pid:
pubs:2350431
Source identifiers:
3549556
Deposit date:
2025-12-09
ARK identifier:
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