Applying Item Response Trees to Personality Data in the Selection Context
Self-report personality scales are used frequently in personnel selection. Traditionally, researchers have assumed that individuals respond to items within these scales using a single-decision process. More recently, a flexible set of item response (IR) tree models have been developed that allow researchers to investigate multiple-decision processes. In the present research, we found that IR tree models fit the data better than a single-decision IR model when fitted to seven self-report personality scales used in a concurrent criterion-related validity study. In addition, we found evidence that the latent variable underlying the direction of a response (agree or disagree) decision process predicted job performance better than latent variables reflecting the other decision processes for the best fitting IR tree model.
LaHuis, D. M.,
Blackmore, C. E.,
Bryant-Lees, K. B.,
& Delgado, K.
(2019). Applying Item Response Trees to Personality Data in the Selection Context. Organizational Research Methods, 22 (4), 1007-1018.