Statistically small effects of the Implicit Association Test can have societally large effects

J Pers Soc Psychol. 2015 Apr;108(4):553-61. doi: 10.1037/pspa0000016. Epub 2014 Nov 17.

Abstract

Greenwald, Poehlman, Uhlmann, and Banaji (2009; GPUB hereafter) reported an average predictive validity correlation of r̄ = .236 for Implicit Association Test (IAT) measures involving Black-White racial attitudes and stereotypes. Oswald, Mitchell, Blanton, Jaccard, and Tetlock (2013; OMBJT) reported a lower aggregate figure for correlations involving IAT measures (r̄ = .148). The difference between the estimates of the 2 reviews was due mostly to their use of different policies for including effect sizes. GPUB limited their study to findings that assessed theoretically expected attitude-behavior and stereotype-judgment correlations along with others that the authors expected to show positive correlations. OMBJT included a substantial minority of correlations for which there was no theoretical expectation of a predictive relationship. Regardless of inclusion policy, both meta-analyses estimated aggregate correlational effect sizes that were large enough to explain discriminatory impacts that are societally significant either because they can affect many people simultaneously or because they can repeatedly affect single persons.

MeSH terms

  • Association*
  • Data Interpretation, Statistical*
  • Humans
  • Meta-Analysis as Topic*
  • Neuropsychological Tests / statistics & numerical data*
  • Racism / psychology*