ESRA 2027 sessions by theme

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Session Details

In social surveys, mixed-mode designs are increasingly common. These designs produce mode effects, including measurement biases - such as social desirability and satisficing - as well as ergonomic and presentation biases. Managing these mode effects has, thus, become a critical challenge. To ensure consistent and reliable statistical results, they must be studied and addressed, both across subpopulations at a single point in time and within the entire surveyed population over time. This session invites submissions that address the identification, quantification, and mitigation - both before and after data collection - of measurement effects, with a focus on both empirical and statistical approaches.
We welcome contributions that apply innovative techniques to detect and estimate the magnitude of measurement effects, accounting for selection factors - usually unmeasured and causing endogeneity problems - that may influence mode preferences. We also encourage submissions that estimate measurement effects across different population subgroups, such as by sex, age, or other demographic characteristics. Additionally, the session seeks papers proposing practical solutions for preventing such effects through tailored questionnaire design or survey methodologies. We’re inviting papers discussing the causality of validated psychometric scales for respondent engagement, openness, and truthfulness in regard to social desirability and satisficing. Finally, we encourage submissions exploring ex-post correction methods, including imputation, calibration, or other statistical adjustments. By fostering dialogue on these issues, the session aims to advance best practices for managing mode effects in survey research.