Analysis of evaluative attributes in a race IAT

Background. The Implicit Association Test (IAT) is the only implicit technique that presents all main characteristics of a real psychological test. We know its main properties and characteristics, some publications serve as a real manual and others as a normative sample. Yet, still not sufficient attention has been paid to the materials used in an IAT. Methods. In this paper, we show that a Many-Facet Rasch model can adequately address this issue, and that even if the evaluative attributes used in an IAT are carefully selected, they might not always be adequate, possibly affecting the quality of measurement. Results. Studying IAT-measured implicit prejudice, we found that, in our sample, implicit ingroup favoritism is slightly stronger than implicit outgroup derogation, that the IAT effect is mainly due to a small sub-sample of all stimuli included in the test, and that associations of faces with good words seem to be slightly stronger than associations of faces with bad words. Conclusions. We argue that post-hoc analyses should be routinely conducted before interpreting the IAT effect. Methodological and theoretical implications of these results are then discussed.