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

Author

Listed:
  • Eric Luis Uhlmann

    (Kellogg [Northwestern] - Kellogg School of Management [Northwestern University, Evanston] - Northwestern University [Evanston])

  • Anthony Greenwald

    (Department of Psychology - University of Washington [Seattle])

  • Andrew Poehlmann

    (Cox School of Management - SMU - Southern Methodist University [Dallas, TX, USA])

  • Mahzarin Banaji

    (Department of Psychology - Harvard University)

Abstract
This review of 122 research reports (184 independent samples, 14,900 subjects) found average r = .274 for prediction of behavioral, judgment, and physiological measures by Implicit Association Test (IAT) measures. Parallel explicit (i.e., self-report) measures, available in 156 of these samples (13,068 subjects), also predicted effectively (average r = .361), but with much greater variability of effect size. Predictive validity of self-report was impaired for socially sensitive topics, for which impression management may distort self-report responses. For 32 samples with criterion measures involving Black–White interracial behavior, predictive validity of IAT measures significantly exceeded that of self-report measures. Both IAT and self-report measures displayed incremental validity, with each measure predicting criterion variance beyond that predicted by the other. The more highly IAT and self-report measures were intercorrelated, the greater was the predictive validity of each.

Suggested Citation

  • Eric Luis Uhlmann & Anthony Greenwald & Andrew Poehlmann & Mahzarin Banaji, 2009. "Understanding and Using the Implicit Association Test: III. Meta-Analysis of Predictive Validity," Post-Print hal-00516146, HAL.
    • Handle: RePEc:hal:journl:hal-00516146
    DOI: 10.1037/a0015575
    as

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