Complex measurements in online self-completion surveys |
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| Coordinator 1 | Dr Cristian Domarchi (University of Southampton) |
| Coordinator 2 | Professor Lisa Calderwood (UCL Centre for Longitudinal Studies) |
| Coordinator 3 | Mr Curtis Jessop (National Centre for Social Research) |
Accurately capturing complex phenomena is critical for the success of social surveys. As the field increasingly shifts towards online data collection, a key challenge emerges: how to administer complex measures without compromising data quality or comparability with other survey modes.
The session is proposed by Research Strand 5 of the Survey Futures* project, “Complex measurement in self-completion surveys” which focuses on how to collect measures of i) industry and occupation ii) event histories and retrospective data iii) consent for data linkage and re-contact and iv) cognitive assessments in self-completion surveys.
Each of these measures presents unique challenges. Ensuring that online participants provide sufficient detail to allow for accurate industry and occupation coding in the absence of interviewer probing can be difficult. Retrospective life history data collected in self-completion surveys may be less complete due to lack of interviewer support. Consent rates for data linkage are consistently lower in online-administered surveys. Adapting cognitive assessments designed for in-person administration for use online may not be feasible or may result in significant mode effects.
This session invites researchers to share insights into how to improve the collection of these and other types of complex measures in online self-completion surveys. We welcome submissions that present evidence on mode and measurement effects in these and other complex measures, as well as findings from trials aimed at enhancing data quality when collecting complex measures in online surveys. Submissions employing experimental designs or other innovative methodologies that can inform future survey strategies are especially encouraged.
*Survey Futures is a UKRI-ESRC funded research programme dedicated to ensuring that large-scale social surveys in the UK can innovate and adapt in an evolving landscape. The programme is a multi-institution collaboration between universities and survey practice organisations.