Detection of Non-Functional Questionnaire Items Using a Binary Logistic Model

Abstract

In the implementation of various questionnaires, it is conceivable that the survey items may not reflect the respondents' thoughts. This situation is regarded as "questionnaire dysfunction," and currently, efforts are being made to design a process for reviewing questionnaire items. In this presentation, as part of the questionnaire redesign, we attempt to detect non-functional questionnaire items using a quantitative approach. Specifically, by employing the binary logistic model adopted in Item Response Theory (IRT), we classify the characteristics of the survey items based on the estimated parameters and enumerate the candidates for the relevant items.