Evaluating the construct validity of Implicit Association Tests using Confirmatory Factor Analytic Models

The Implicit Association Test (IAT) is the most widely used method for assessing implicit bias and prejudice. By avoiding the need for introspection, the IAT is suggested to be a more valid indicator of prejudice than explicit measures of attitudes (i.e. questionnaires). However, implicit attitudinal literature has demonstrated highly variable associations between IAT scores and various outcomes. Such inconsistencies imply IAT scores may be significantly influenced by measurement error, which could thwart efforts to accurately estimate underlying attitudes. The aim of the present thesis was to examine the construct validity of the IAT using Confirmatory Factor Analytic models (CFA) to account for the confounding influences of measurement error. Three studies examined various aspects of the validity of IATs using data from 198 student participants of the University of Tasmania, Australia. Study One assessed the internal consistency and internal convergent validity of traditional verbal IATs, fully pictorial IATs and Affective Priming Tasks (APTs) using single-group CFA. The study revealed high amount of random error variance in the implicit attitudinal data, comprising around 55% of IAT scores and 95% of APT scores. Despite the high proportion of random error, the IATs appeared to consistently assess the trait attitude constructs, though this was not true for the APTs. The APTs were consequently deemed invalid measures of implicit attitudes.