Running Head: IMPROVED SCORING OF THE IAT UNDERSTANDING AND USING THE IMPLICIT ASSOCIATION TEST: 1. AN IMPROVED SCORING ALGORITHM

In reporting Implicit Association Test (IAT) results, researchers have most often used scoring conventions described in the first publication of the IAT (A. G. Greenwald, D. E. McGhee, & J. L. K. Schwartz, 1998). Demonstration IATs available on the Internet have produced large data sets that were used here to evaluate alternative scoring procedures. Candidate new algorithms were examined in terms of their (a) correlations with parallel selfreport measures, (b) resistance to an artifact associated with speed of responding, (c) internal consistency, (d) sensitivity to known influences on IAT measures, and (e) resistance to known procedural influences. The best-performing measure incorporates data from the IAT’s practice trials, uses a metric that is calibrated by each respondent’s latency variability, and includes a latency penalty for errors. This new algorithm strongly outperforms the earlier (conventional) procedure. Greenwald, Nosek, & Banaji: Improved Scoring of the IAT Draft of March 10, 2003 Page -3The Implicit Association Test (IAT) provides a measure of strengths of automatic associations. This measure is computed from performance speeds at two classification tasks in which association strengths influence performance. The apparent usefulness of the IAT may be due to its combination of apparent resistance to self-presentation artifact (Banse, Seise, & Zerbes, 2001; Egloff & Schmukle, 2002; Kim & Greenwald, 1998), its lack of dependence on introspective access to the association strengths being measured (Greenwald, Banaji, Rudman, Farnham, Nosek, & Mellott, 2002), and its ease of adaptation to assess a broad variety of socially significant associations (see overview in Greenwald & Nosek, 2001). The IAT’s measure, often referred to as the IAT effect, is based on latencies for two tasks that differ in instructions for using two response keys to classify four categories of stimuli. Table 1 describes the seven steps of a typical IAT procedure. The first IAT publication (Greenwald, McGhee, & Schwartz, 1998) introduced a scoring procedure that has been used in the majority of subsequently published studies. The features of this conventional algorithm (see Table 7) include (a) dropping the first two trials of trial blocks for the IAT’s two classification tasks (Blocks 4 and 7 in Table 1), (b) recoding latencies outside of lower (300 ms) and upper (3,000 ms) boundaries to those boundary values, (c) logtransforming latencies before averaging them, (d) including error-trial latencies in the analyzed data, and (e) not using data from respondents for whom average latencies or error rates appear to be unusually high for the sample being investigated. The main justification for originally using these conventional procedures was that, compared with several alternative procedures often used with latency data, the conventional procedures typically yielded larger statistical effect