Structural Bias in Stylized Items with Point-Valued Categories: A Calibrated Approach

Survey research frequently relies on stylized questions with discrete, ordered response categories to measure behaviors or attitudes. While these items simplify responses and facilitate standardization, they introduce a structural bias component (SBC) arising from the discrepancy between actual behavior and the assigned category val- ues. This paper investigates SBC in the context of religious practice, using data from the European Values Study across multiple waves and countries. The analysis shows that the discrete nature of point- value items can generate distortions. A calibration model is proposed to estimate and adjust for this bias, assuming a uniform distribution of behaviors within each interval. Findings suggest that, while SBC can reach substantial levels in some domains—particu- larly where the accuracy of absolute values is crucial—in practice, however, its impact on theoretical interpretations or explanatory fac- tors is typically limited. The study underscores the importance of carefully designing response categories and considering alternative scaling methods, such as stylized items with interval-valued catego- ries, to reduce measurement error and enhance survey validity.