Distinguishing Between Models for Extreme and Midpoint Response Styles as Opposite Poles of a Single Dimension versus Two Separate Dimensions: A Simulation Study.

Abstract

Extreme and midpoint response styles have frequently been found to decrease the validity of Likert-type questionnaire results. Different approaches for modelling extreme and midpoint responding have been proposed in the literature, with some advocating for a unidimensional conceptualization of the response styles as opposite poles, and others modelling them as separate dimensions. How these response styles are modelled influences the estimation complexity, parameter estimates, and detection of and correction for response styles in IRT models. For these reasons, we examine if it is possible to empirically distinguish between extreme and midpoint responding as two separate dimensions versus two opposite sides of a single dimension. The various conceptualizations are modelled using the multidimensional nominal response model, with the AIC and BIC being used to distinguish between the competing models in a simulation study and an empirical example. Results indicate good performance of both information criteria given sufficient sample size, test length, and response style strength. The BIC outperformed the AIC in cases where no response styles were present, while the AIC outperformed the BIC in cases where multiple response style dimensions were present. Implications of the results for practice are discussed.