Applying Unidimensional Models for Semiordered Data to Scale Data With Neutral Responses

Abstract

The purpose of this study is to evaluate whether a recently developed semiordered model can be used to explore the functioning of neutral response options in rating scale data. Huggins-Manley, Algina, and Zhou developed a class of unidimensional models for semiordered data within scale items (i.e., items with both ordered response categories and an additional nominal response category) and found promising results when applying them to scale data with Not Applicable response categories. In this study, we extended the application of the semi–partial credit model (PCM) to evaluate whether the semi-PCM can be used to calibrate potentially unordered neutral responses in rating scale data, and if so, how the approach compares with alternate methods of dealing with the neutral response option. Findings indicate that the semi-PCM can (a) assist practitioners in evaluating the ordered or unordered nature of neutral responses and (b) provide a viable alternative for θ estimation in the presence of an unordered neutral category. The process used in this study also provides a methodological framework for researchers and practitioners to use when dealing with neutral responses in their own data.