Supplemental Material for Understanding and Using the Implicit Association Test: III. Meta-Analysis of Predictive Validity

2009 ◽  
Keyword(s):  
Predictive Validity ◽  
Implicit Association Test ◽  
Meta Analysis ◽  
Association Test ◽  
Implicit Association

Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity.

2009 ◽  
Vol 97 (1) ◽  
pp. 17-41 ◽  
Author(s):  
Anthony G. Greenwald ◽  
T. Andrew Poehlman ◽  
Eric Luis Uhlmann ◽  
Mahzarin R. Banaji
Keyword(s):  
Predictive Validity ◽  
Implicit Association Test ◽  
Meta Analysis ◽  
Association Test ◽  
Implicit Association

scholarly journals Cognitive Control and the Implicit Association Test: A Replication of Siegel, Dougherty, and Huber (2012)

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
David J. Johnson ◽  
David Ampofo ◽  
Serra A Erbas ◽  
Alison Robey ◽  
Harry Calvert ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Implicit Association Test ◽  
Null Hypothesis ◽  
Experimental Social Psychology ◽  
Meta Analysis ◽  
Original Study ◽  
Association Test ◽  
Implicit Association ◽  
False Feedback ◽  
Control Versus

The implicit association test (IAT) is widely used to measure evaluative associations towards groups or the self but is influenced by other traits. Siegel, Dougherty, and Huber (2012, Journal of Experimental Social Psychology) found that manipulating cognitive control via false feedback (Study 3) changed the degree to which the IAT was related to cognitive control versus evaluative associations. We conducted two replications of this study and a mini meta-analysis. Null-hypothesis tests, meta-analysis, and a small telescope approach demonstrated weak to no support for the original hypotheses. We conclude that the original findings are unreliable and that both the original study and our replications do not provide evidence that manipulating cognitive control affects IAT scores.

scholarly journals Measure What You are Trying to Predict: Applying the Correspondence Principle to the Implicit Association Test

2019 ◽  
Author(s):  
Louis H. Irving ◽  
Colin Smith
Keyword(s):  
Predictive Validity ◽  
Implicit Association Test ◽  
Correspondence Principle ◽  
Association Test ◽  
Future Research ◽  
Implicit Association ◽  
Implicit Measures ◽  
Total N ◽  
Single Target ◽  
Explicit Measures

The Implicit Association Test (IAT) is nearly synonymous with the implicit attitude construct. At the same time, correlations between the IAT and criterion measures are often remarkably low. Developed within research using explicit measures of attitudes, the correspondence principle posits that measures should better predict criteria when there is a match in terms of the level of generality or specificity at which both are conceptualized (Ajzen & Fishbein, 1977). As such, weak implicit-criterion correlations are to be expected when broad general implicit measures are used to predict highly specific criteria. Research using explicit measures of attitudes consistently supports the correspondence principle, but conceptual correspondence is rarely considered by researchers using implicit measures to predict behavior and other relevant criterion measures. In five experiments (total N = 4650), we provide the first direct evidence demonstrating the relevance of the correspondence principle to the predictive validity of the IAT and Single Target IAT. That said, it is not the case that the IAT always predicts criteria better when correspondence is high. Inconsistency across the pattern of results suggests there is much more that remains to be understood about the relevance of the correspondence principle to the implicit-criterion relationship. Taken together, however, our findings suggest that conceptual correspondence typically increases (and never decreases) the magnitude of implicit-behavior and implicit-explicit relationships. We provide a framework for future research necessary to establish when correspondence is more likely to increase the predictive validity of measures such as the IAT.

scholarly journals Relationship between the Implicit Association Test and intergroup behavior: A meta-analysis.

2019 ◽  
Vol 74 (5) ◽  
pp. 569-586 ◽  
Author(s):  
Benedek Kurdi ◽  
Allison E. Seitchik ◽  
Jordan R. Axt ◽  
Timothy J. Carroll ◽  
Arpi Karapetyan ◽  
...  
Keyword(s):  
Implicit Association Test ◽  
Meta Analysis ◽  
Association Test ◽  
Implicit Association ◽  
Intergroup Behavior

scholarly journals Meta-Analytic Use of Balanced Identity Theory to Validate the Implicit Association Test

2020 ◽  
pp. 014616722091663 ◽  
Author(s):  
Dario Cvencek ◽  
Andrew N. Meltzoff ◽  
Craig D. Maddox ◽  
Brian A. Nosek ◽  
Laurie A. Rudman ◽  
...  
Keyword(s):  
Implicit Association Test ◽  
Statistical Power ◽  
Identity Theory ◽  
Meta Analysis ◽  
Association Test ◽  
Self Report ◽  
Implicit Association ◽  
Individual Subject ◽  
Data Set ◽  
Total N

This meta-analysis evaluated theoretical predictions from balanced identity theory (BIT) and evaluated the validity of zero points of Implicit Association Test (IAT) and self-report measures used to test these predictions. Twenty-one researchers contributed individual subject data from 36 experiments (total N = 12,773) that used both explicit and implicit measures of the social–cognitive constructs. The meta-analysis confirmed predictions of BIT’s balance–congruity principle and simultaneously validated interpretation of the IAT’s zero point as indicating absence of preference between two attitude objects. Statistical power afforded by the sample size enabled the first confirmations of balance–congruity predictions with self-report measures. Beyond these empirical results, the meta-analysis introduced a within-study statistical test of the balance–congruity principle, finding that it had greater efficiency than the previous best method. The meta-analysis’s full data set has been publicly archived to enable further studies of interrelations among attitudes, stereotypes, and identities.

Motivational Relevance Modulates the Predictive Validity of the Implicit Association Test

2020 ◽  
Vol 38 (3) ◽  
pp. 234-265
Author(s):  
Cristina Zogmaister ◽  
Juliette Richetin ◽  
Marco Perugini ◽  
Michela Vezzoli ◽  
Giulia Songa
Keyword(s):  
Predictive Validity ◽  
Implicit Association Test ◽  
Association Test ◽  
Implicit Association
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