A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories. (December 2021)

• Record Type: Journal Article
• Authors: Colombi, Roberto; Giordano, Sabrina; Tutz, Gerhard
• Is Part Of: Journal of educational and behavioral statistics. Volume 46:Number 6(2021)
• Page Start: 682
• Page End: 716
• Publication Date: 2021-12
• Subjects: logit models -- latent variables -- marginal models -- response styles; Educational statistics -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 370.2
• DOI: 10.3102/1076998621992554
• Languages: English
• ISSNs: 1076-9986

Abstract

A mixture of logit models is proposed that discriminates between responses to rating questions that are affected by a tendency to prefer middle or extremes of the scale regardless of the content of the item (response styles) and purely content-driven preferences. Explanatory variables are used to characterize the content-driven way of answering as well as the tendency to middle or extreme categories. The proposed model is extended to account for the presence of response styles in the case of several items, and the association among responses is described, both when they are content driven or dictated by response styles. In addition, stochastic orderings, related to the tendency to select middle or extreme categories, are introduced and investigated. A simulation study describes the effectiveness of the proposed model, and an application to a questionnaire on attitudes toward ethnic minorities illustrates the applicability of the modeling approach.