Applying Item Response Trees to Personality Data in the Selection Context. (October 2019)

• Record Type: Journal Article
• Authors: LaHuis, David Michael; Blackmore, Caitlin E.; Bryant-Lees, Kinsey Blue; Delgado, Kristin
• Is Part Of: Organizational research methods. Volume 22:Number 4(2019:Oct.)
• Page Start: 1007
• Page End: 1018
• Publication Date: 2019-10
• Subjects: item response theory -- quantitative research -- survey research -- quantitative research -- measurement design -- research design; Organization -- Research -- Methodology -- Periodicals; Organizational sociology -- Research -- Methodology -- Periodicals; Management -- Research -- Methodology -- Periodicals; 302.350721
• DOI: 10.1177/1094428118780310
• Languages: English
• ISSNs: 1094-4281

Abstract

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.