ESRA 2027 sessions by theme

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As self-administered surveys become increasingly prevalent, ensuring that the intended respondent is the person who actually completes the questionnaire has become an important methodological challenge. In individually named samples, invitation mailings include a unique access code or link to an online questionnaire, a paper questionnaire, or both. Once a completed questionnaire is returned, it is generally assumed that it has been completed by the intended respondent. In practice, however, survey organisations have little control over who within a household actually completes the survey after the invitation has been delivered.
Similar issue arise in address-based household surveys where a specific household member must be selected to participate. Respondent selection may be carried out incorrection, intentionally or unintentionally, without the knowledge of the survey organisation. In longitudinal studies, it is essential that the same individual respond at each wave, yet another household member may complete the questionnaire instead. Such respondent substitution may result from respondents overlooking instructions, misunderstanding the selection procedure, or deliberately deviating from the protocol.
Respondent substitution has the potential to threaten data quality and the validity of survey estimates if it occurs systematically. Despite its importance, relatively little is known about the prevalence of incorrect respondents, the circumstances under which substitution occurs, and effective approach for preventing, detecting and reporting it.
This session welcomes contributions addressing the issue of incorrect or ‘wrong’ respondents in probability-based self-completion surveys. Topics include, but are not limited to:
• Methods for detecting respondent substitution and identifying incorrect respondents.
• Evidence on the prevalence, determinants and consequences of respondent substitution.
• The impact of ‘wrong’ respondents and protocol non-compliance on sample composition, non-response bias and data quality.
• Design features and operational strategies to prevent or reduce respondent substitution.
• Ethical and practical considerations related to respondent verification and protocol compliance.