Understanding and Using the Brief Implicit Association Test: Recommended Scoring Procedures

A brief version of the Implicit Association Test (BIAT) has been introduced.The present research identified analytical best practices for overall psychometric performance of the BIAT.In 7 studies and multiple replications, we investigated analytic practices with several evaluation criteria: sensitivity to detecting known effects and group differences, internal consistency, relations with implicit measures of the same topic, relations with explicit measures of the same topic and other criterion variables, and resistance to an extraneous influence of average response time.The data transformation algorithms D outperformed other approaches.This replicates and extends the strong prior performance of D compared to conventional analytic techniques.We conclude with recommended analytic practices for standard use of the BIAT. Understanding and Using the Brief Implicit Association Test: I. Recommended Scoring ProceduresEven the most brilliant research ideas can flounder if data collection procedures and data analytic strategies applied in the pursuit of these ideas are suboptimal.Research efficiency, the knowledge gained in proportion to resources invested, can be improved by maximizing the quality of procedural and analytical methods.Numerous paradigms in mental chronometry, such as Stroop and lexical-decision tasks, define constructs derived from contrasting response latencies between performance conditions [1].The Implicit Association Test (IAT) [2] is a