Title: The Use of Paradata (Field Process Data) in Cross-Sectional and Longitudinal Surveys
Funder: Economic and Social Research Council

Abstract: During the last twenty years survey data are increasingly collected through computer assisted modes. As a result, a new class of data, so-called paradata, is now available to survey methodologists. Paradata are a by-product of the data collection process capturing information about that process. Typical examples are interviewer observations about a sampled household and its surrounding neighbourhood, interviewer call record data, capturing information such as date and time of each call attempt to a household, and key-stroke files, capturing the navigation through the questionnaire. To date, paradata have most prominently been used to study nonresponse in cross-sectional surveys, an increasing problem for research in the social sciences. If a significant fraction of individuals or households selected for a survey does not take part, the quality of the resulting data is lowered. Less information is collected, leading to increased uncertainty in the results, and there is the danger that respondents are not representative of all selected units. This in turn damages analyses based on the data. If respondents are not a representative group there are likely to be biases in sample-based estimates. Over recent years, awareness of the potential benefits of paradata has grown amongst both data producers and data users and this has been reflected in special interest and invited paper sessions at national and international conferences. However, examples of successful applications and discussions of methodological issues around the use of paradata have not yet been widely published. The use of paradata and its benefits are still largely unexplored for many aspects of survey research and modelling issues are not well understood. In particular, the benefits for fieldwork and cost savings for longitudinal surveys have not yet been investigated. This project aims to address these shortcomings. The key objectives of this research are to explore the uses of paradata for longitudinal surveys with the aim of improving field process management and intervention decisions during data collection. The methodological development on how best to use such paradata in statistical models, including for example in nonresponse adjustment and in statistical models based on paradata, will play another key area. The research will be organised into three sub-projects which will: 1) investigate the use of call record data and interviewer observations to study nonresponse in longitudinal surveys, 2) provide insights into the effects of interviewing strategies and other interviewer attributes on response in longitudinal surveys, and 3) gain knowledge about the measurement error properties of paradata, in particular interviewer observations. All three subprojects will make use of already existing rich paradata collected for longitudinal and cross-sectional surveys in the UK and the US. Analysis techniques will include multilevel, discrete-time event history and longitudinal data analysis methods, to, for example, account for the clustering of sample units within interviewers. The project will make use of recent advances in the methodology of multilevel modelling by the Lemma node of the ESRC National Centre for Research Methods. Benefits of this research will include the design of efficient calling behaviours and strategies, improved interviewer training and interviewer allocations, cost savings and efficiency improvements in data collection processes, specification of models and advances in the theoretical framework of paradata. The project team will work closely together with a range of statistical agencies nationally and internationally to ensure the benefits of this research for survey practice. Dissemination will include a short course (which will be part of the training programme of the ESRC National Centre for Research Methods, such as part of CASS (Courses in Applied Social Surveys)) and an international workshop on paradata.


Research activity codes: 1.4 METHODOLOGIES AND MEASUREMENTS;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE