Build custom Implicit Association Tests for bias and attitude research in minutes. Standard 7-block design with automatic D-score calculation. No coding required.
The Implicit Association Test (IAT), developed by Anthony Greenwald and colleagues in 1998, is the most widely used measure of implicit attitudes and unconscious bias. It has been featured in thousands of peer-reviewed publications.
The IAT measures the strength of associations between concepts (e.g., racial groups, gender) and evaluations (e.g., good/bad) or attributes (e.g., career/family). Response time differences reveal implicit biases that may differ from explicit self-reports.
Faster RTs indicate stronger associations
AssessKit automatically generates all 7 blocks with proper counterbalancing
Visual editor for creating IATs. No need for iatgen, Inquisit, or JavaScript.
Built-in D-score calculation following Greenwald et al. (2003) improved algorithm.
Use faces, objects, or words. Upload custom images for your research needs.
Automatic block order counterbalancing for rigorous experimental design.
Measure evaluative associations (good/bad, pleasant/unpleasant) with target concepts like racial groups, brands, or objects.
Measure associations between groups and stereotypical attributes (e.g., gender and career/family, age and competence).
Measure implicit self-associations with traits, identities, or evaluations (self-esteem IAT, identity IATs).
The IAT, developed by Greenwald et al. (1998), measures implicit associations between concepts (e.g., race, gender) and evaluations (good/bad) or stereotypes. It reveals automatic attitudes that people may not consciously endorse or report.
The IAT compares response times across two conditions: one where target concepts share a response key with positive attributes, and one where they share a key with negative attributes. Faster responses indicate stronger implicit associations.
The standard IAT uses 7 blocks: (1) target discrimination, (2) attribute discrimination, (3-4) combined task with one pairing, (5) reversed target discrimination, (6-7) combined task with reversed pairing. AssessKit automatically generates this structure.
Yes. AssessKit supports both image and text stimuli for IAT categories. You can mix images (faces, objects) with text words to create comprehensive IAT measures.
AssessKit automatically calculates the IAT D-score following the improved scoring algorithm (Greenwald et al., 2003), including built-in latency penalties, error penalties, and practice/test block weighting.
Create custom Implicit Association Tests for your research. Free to start, no credit card required.
Get Started Free