Distinguishing differences in construct from differences in response style: gsem for item response theory models with anchoring vignettes

Andrew Pickles (), Matt Bluett-Duncan (), Helen Sharp () and Silia Vitoratou ()
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Andrew Pickles: King’s College London
Matt Bluett-Duncan: University of Manchester
Helen Sharp: University of Liverpool
Silia Vitoratou: King’s College London

Stata Journal, 2024, vol. 24, issue 4, 666-686

Abstract: Item response theory models allow estimation of participant and group-mean trait scores from responses to a set of items, but estimates can be biased when participants vary in their response style. We illustrate models fit in gsem that can account for such response style differences by comparing self-report with their ratings of anchoring vignettes—descriptions of other individuals displaying different levels of the trait. Simulation results from standard item response the- ory, mean bias, random bias, and free-threshold models are illustrated. We show that unbiased estimates can be recovered when the vignettes rated depend on the participants’ own self-rating or are even rated by a different sample, substantially broadening their scope of application.

Keywords: item response theory; IRT; anchoring vignettes; response bias; cross-culture calibration (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1177/1536867X241297920

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