Continuous Rating Scale Analytics (CoRSA): A tool for analyzing continuous and discrete data with item response theory

The use of continuous rating scales such as the visual analogue scale (VAS) in research has increased, yet they are less popular than discrete scales like the Likert scale. The non-popularity of continuous scales is primarily due to the lack of validated analytical tools and user-friendly interfaces, which have also jointly resulted in a lack of sufficient theoretical and empirical research supporting confidence in using continuous rating formats. This research aims to address these gaps through four studies. The first study proposed an algorithm and developed the Continuous Rating Scale Analytics (CoRSA) to estimate parameters for the continuous rating scale model (Müller, Psychometrika, 52, 165–181, 1987). The second study evaluated CoRSA’s efficacy in analyzing continuous scores compared to pcIRT (Hohensinn, Journal of Statistical Software, 84, 1–14, 2018) and discrete scores against ConQuest (Adams et al., 2020). Results showed superior parameter recovery with CoRSA for continuous data and comparable outcomes for discrete data. The third study analyzed empirical data from career interest and work value assessments using both VAS and Likert scales with CoRSA, demonstrating good model-data fit and validating CoRSA’s effectiveness in rescaling data to interval measurements. Finally, the fourth study integrated CoRSA into the VAS-RRP 2.0 platform (Sung & Wu, Behavior Research Methods, 50, 1694–1715, 2018) to enhance accessibility and usability, allowing researchers and practitioners unfamiliar with statistical procedures to easily analyze continuous data. These findings confirm CoRSA as a valid tool for analyzing both continuous and discrete data, enhancing the utility of continuous rating formats in diverse research contexts.