Caroline Vandenplas

Devenir parents ré-active les inégalités de genre: une analyse des parcours de vie des hommes et des femmes en Suisse

Response rates are declining increasing the risk of nonresponse error. The reasons for this decline are multiple: the rise of online surveys, mobile phones, and information requests, societal changes, greater awareness of privacy issues, etc. To combat this decline, fieldwork efforts have become increasingly intensive: widespread use of respondent incentives, advance letters, and an increased number of contact attempts. In addition, complex fieldwork strategies such as adaptive call scheduling or responsive designs have been implemented. The additional efforts to counterbalance nonresponse complicate the measurement of the increased difficulty of contacting potential respondents and convincing them to cooperate. To observe developments in response rates we use the first seven rounds of the European Social Survey, a biennial face-to-face survey. Despite some changes to the fieldwork efforts in some countries (choice of survey agency, available sample frame, incentives, number of contact attempts), many characteristics have been stable: effective sample size, (contact and) survey mode, and questionnaire design. To control for the different country composition in different rounds, we use a multilevel model with countries as level 2 units and response rates in each country-year combination as level 1 units. The results show a declining trend, although only round 7 has a significant negative effect.

Fieldwork Monitoring for the European Social Survey: An illustration with Belgium and the Czech Republic in Round 7

Abstract Adaptive and responsive survey designs rely on monitoring indicators based on paradata. This process can better inform fieldwork management if the indicators are paired with a benchmark, which relies on empirical information collected in the first phase of the fieldwork or, for repeated or longitudinal surveys, in previous rounds or waves. We propose the “fieldwork power” (fieldwork production per time unit) as an indicator for monitoring, and we simulate this for the European Social Survey (ESS) Round 7 in Belgium and in the Czech Republic. We operationalize the fieldwork power as the weekly number of completed interviews and of contacts, the ratio of the number of completed interviews to the number of contact attempts and to the number of refusals. We use a repeated measurement multilevel model, with surveys in the previous rounds of the European Social Survey as the macro level and the weekly fieldwork power as repeated measurements to create benchmarks. We also monitor effort and data quality metrics. The results show how problems in the fieldwork evolution can be detected by monitoring the fieldwork power and by comparing it with the benchmarks. The analysis also proves helpful regarding post-survey fieldwork evaluation, and links effort, productivity, and data quality.