Identifying Response Styles: A Latent-Class Bilinear Multinomial Logit Model

Abstract

Respondents can vary strongly in the way they use rating scales. Specifically, respondents can exhibit a variety of response styles, which threatens the validity of the responses. The purpose of this article is to investigate how response style and content of the items affect rating scale responses. The authors develop a novel model that accounts for different types of response styles, content of items, and background characteristics of respondents. By imposing a bilinear parameter structure on a multinomial logit model, the authors graphically distinguish the effects on the response behavior of the characteristics of a respondent and the content of an item. The authors combine this approach with finite mixture modeling, yielding two segmentations of the respondents: one for response style and one for item content. They apply this latent-class bilinear multinomial logit model to the well-known List of Values in a cross-national context. The results show large differences in the opinions and the response styles of respondents and reveal previously unknown response styles. Some response styles appear to be valid communication styles, whereas other response styles often concur with inconsistent opinions of the items and seem to be response bias.

Should we trust survey data? Assessing response simplification and data fabrication

“…Oskamp (1977: 37) defined response styles as "systematic ways of answering which are not directly related to the question content". A large literature has identified various response tendencies such as acquiescence, selecting the extreme options, mid-point responding, limited response differentiation, and random or arbitrary responding (Aichholzer, 2013;Baumgartner and Steenkamp, 2001;Van Rosmalen, van Herk and Groenen, 2010;Watkins and Cheung, 1995). Controlling for response styles is particularly important for cross-cultural studies, since response styles have been found to vary by both race and culture (Bachman and O'Malley, 1984;Dayton, Zhan, Sangl, Darby, and Moy, 2006;Hamamura, Heine, and Paulhus, 2008;Hui and Triandis, 1989).…”

Multiscale Measurement of Extreme Response Style

“…A latent class mixture approach has been taken by a number of other researchers as well (Maij-de Meij, Kelderman, & van der Flier, 2008;Rost, Carstensen, & von Davier, 1997;van Rosmalen, van Herk, & Groenen, 2010). Although such approaches are useful in the exploratory study of response style, they offer less in terms of their ability to adjust trait estimates in response to response style effects at the individual level.…”

The calibrated sigma method: An efficient remedy for between-group differences in response category use on Likert scales

“…But the approach is more general and can be used whenever there are concerns that a group-level confound may invalidate comparisons across groups. First, response style research has shown that a substantial proportion of response style variation occurs at the country level (De Jong, et al, 2008;Van Rosmalen, Van Herk, & Groenen, 2010), so it is possible that even when optimally equivalent response category labels are used in cross-national research, respondents from different nationalities use response scales differently. Second, cross-group differences in scale usage are prevalent in contexts other than cross-national survey research.…”