ESRA 2027 sessions by theme

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Session Details

Panel attrition remains a persistent methodological challenge in panel and longitudinal survey research. With the availability of rich paradata, the integration of auxiliary and register data, and advances in analytical methods, new opportunities arise not only to understand why respondents drop out, but also to anticipate and address attrition. This session adopts a lifecycle perspective on panel attrition by addressing three interconnected pillars: Prevention, Prediction, and Mitigation. We invite empirical, methodological, and practical contributions that advance research on panel retention across all three stages:

Prevention: Approaches to prevent or reduce attrition before and during fieldwork, including incentive structures, contact and communication strategies, respondent burden reduction, push-to-web and mode-switching designs, and between-wave panel maintenance.

Prediction: Approaches to identify respondents at risk of attrition at an early stage, using data from ongoing fieldwork and previous waves to identify risk groups and estimate attrition probabilities, and inform timely interventions. This includes the use of paradata and participation behaviour (e.g., response times, contact histories, device use), auxiliary information, and predictive models.

Mitigation: Approaches to address attrition and limit its consequences for data quality, particularly where attrition is selective, once dropout has occurred, including targeted re-engagement activities for temporary nonrespondents, sample replenishment, weighting adjustments, imputation, and the use of administrative or register data to assess and address potential attrition bias.

The session brings together researchers and panel managers working across different types of longitudinal surveys and panel infrastructures. By connecting research on prevention, prediction, and mitigation, it aims to foster discussion on how new data sources and analytical methods can support a more proactive and data-informed approach to panel maintenance.
Comparative, experimental, and applied studies across different panel designs and longitudinal survey infrastructures are particularly welcome.