The role of attitude features in the reliability of IAT scores

Researchers commonly use the Implicit Association Test (IAT) to assess the automatic attitudes of individuals and groups. Although contended by some, the IAT is used in large part due to its psychometric properties, which are generally superior relative to most other measures of automatic cognition. Much focus has therefore been dedicated to the IAT's psychometric properties (particularly its internal consistency). However, this work has focused near-exclusively on moderators based on the procedural features of the IAT itself, and little on the varying properties of the construct under investigation within the measure. This is despite the fact that attitude features have already been demonstrated to influence explicit attitude measures. Here, we intend to investigate whether different attitude features can effectively predict the internal consistency of IAT scores using a largescale IAT dataset (lowest N = 30,161, highest N = 30,502). We find that five of six attitude features (personal importance, degree of thinking, certainty, self-concept, and most strongly polarity) are positively related to the reliability of the IAT. Our findings have significant implications for the way in which the IAT's reliability has been conceived.