An application of Many-Facet Rasch Model to the analysis of an implicit associate test
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The article aims to measure implicit gender-science stereotype of female and male individuals. A Many-Facet Rasch Measurement analysis was used to disentangle the contribution of specific associations to the overall IAT measure. A preference for associating males with science and females with liberal arts is observed in both gender groups. Male participants show stronger stereotype than female participants, and this preference is driven primarily by associating males with science rather than females with liberal arts. Besides, some stimulus words played different roles to the overall IAT effects. This research supported that MFRM is a useful method for exploring IAT. As consequences, we argue that researchers should be more careful when choosing stimulus for IAT and interpreting IAT effects.