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- Title
Filling the Gap Between Implicit Associations and Behavior: A Linear Mixed-Effects Rasch Analysis of the Implicit Association Test.
- Authors
Epifania, Ottavia M.; Anselmi, Pasquale; Robusto, Egidio
- Abstract
The measure obtained from the Implicit Association Test (IAT; Greenwald et al., 1998. DOI: 10.1037/0022-3514.74.6.1464) is often used to predict people's behaviors. However, it has shown poor predictive ability potentially because of its typical scoring method (the D score), which is affected by the across-trial variability in the IAT data and might provide biased estimates of the construct. Linear Mixed-Effects Models (LMMs) can address this issue while providing a Rasch-like parametrization of accuracy and time responses. In this study, the predictive abilities of D scores and LMM estimates were compared. The LMMs estimates showed better predictive ability than the D score, and allowed for in-depth analyses at the stimulus level that helped in reducing the acrosstrial variability. Implications of the results and limitations of the study are discussed.
- Publication
Methodology: European Journal of Research Methods for the Behavioral & Social Sciences, 2022, Vol 18, Issue 3, p185
- ISSN
1614-1881
- Publication type
Academic Journal
- DOI
10.5964/meth.7155