This study provides a synopsis of the current fieldwork monitoring practices of large-scale surveys in Germany. Based on the results of a standardized questionnaire, the study summarizes fieldwork monitoring indicators used and fieldwork measures carried out by 17 large-scale social sciences surveys in Germany. Our descriptive results reveal that a common set of fieldwork indicators and measures exist on which the studied surveys rely. However, it also uncovers the need for additional design-specific indicators. Finally, it underlines the importance of a close cooperation between survey representatives and fieldwork agencies to optimize processes in fieldwork monitoring in the German survey context. …

Cross-national surveys face the particular challenge of trying to balance optimal survey quality within a country with comparability across countries in terms of data quality. Addressing this challenge during fieldwork requires effective management of fieldwork data, a task made more difficult by the inherent differences between countries. This article argues that changes to the comprehensiveness, timeliness, consistency, and accessibility of fieldwork data facilitate monitoring and represent a necessary step forward towards achieving optimal data quality in cross-national surveys. It discusses the approach of the European Social Survey (ESS) for monitoring fieldwork cross-nationally, and specifically, the improvements made to central monitoring …

Auxiliary data are becoming more important as nonresponse rates increase and new fieldwork monitoring and respondent targeting strategies develop. In many cases, auxiliary data are collected or linked to the gross sample to predict survey response. If the auxiliary data have high predictive power, the response models can meaningfully inform survey operations as well as post-survey adjustment procedures. In this paper, I examine the utility of different sources of auxiliary data (sampling frame data, interviewer observations, and micro-geographic area data) for modeling survey response in a probability-based online panel in Germany. I find that the utility of each of these …

Using paradata to modify design features during fieldwork is the earmark of responsive designs (Groves & Heeringa, 2006). One objective of responsive approaches is to improve the composition of the final sample by gaining the participation of nonrespondents. A simple but innovative attempt at realizing such a response intervention was undertaken during the fieldwork of PIAAC Germany 2012. Different groups of nonrespondents were identified for follow-up efforts. With a view to the outcome measures of PIAAC, basic skills of the adult population, two groups were focused: Non-nationals and sample persons with low educational attainment. To identify these groups, different sources …