Caroline Roberts is a Senior Lecturer and Researcher in quantitative research methods based in the Institute of Social Sciences at the University of Lausanne (UNIL), Switzerland. She is also an Affiliated Researcher/ Survey Methodologist at FORS, the Swiss Centre of Expertise in the Social Sciences and the Swiss Centre of Expertise in Life Course Research. She co-leads a research programme on survey methodology as part of the 'Developments in Research and Methods in the Social Sciences (DReMSS)' platform at UNIL. Caroline is a specialist in survey methodology and questionnaire design, and the design and implementation of survey experiments.
She has a PhD in Social Psychology from the London School of Economics and Political Science, which focused on British social attitudes towards European integration and challenges involved in measuring public opinion in surveys. She has extensive professional experience in survey research, gained in coordinating teams of large-scale surveys at the UK's Office for National Statistics, the European Social Survey HQ at City University, and on the American National Election Studies at Stanford University. At UNIL, she collaborates closely with researchers at FORS on methodological research linked to their large-scale national and international surveys, including the Swiss Election Studies (Selects), the Swiss Household Panel Survey, the European Social Survey, and MOSAiCH-ISSP. She teaches courses on survey research methods, questionnaire design, social attitude measurement, and introductory quantitative research methods. She also regularly teaches specialist ad hoc short courses on survey methodology, and provides further education training on data literacy for school teachers. Caroline is currently Chair of the Methods Advisory Board of the European Social Survey ERIC. From 2015-2021, she served on the Committee of the European Survey Research Association (ESRA), serving notably, as Conference Chair for the 2019 ESRA conference, and as ESRA President from 2019-2021.
Research Interests
Caroline's research interests relate to the measurement and reduction of survey errors, particularly in the context of mixed mode and mixed device data collection. She has been involved in multiple projects linked to large-scale surveys investigating ways to address nonresponse and the effects of mixing modes of data collection on data quality. Her current research is focused on challenges around the integration of digital data collection in surveys (particularly using smartphone apps), and in particular, the role of data privacy concerns and digital trust. Her work is mostly based on primary data collection involving large-scale experiments embedded in general population, probability-based sample surveys. Recent studies have investigated optimal of ways of recruiting participants to an app-based panel study; willingness to donate smartphone data and share photographs in surveys; effects of data protection information on trust and participation in an online panel; barriers to participation in an app-based time-use study; and ways to improve public engagement in social research. She is currently involved as an international consultant in the ESRC-funded Survey Data Collection Methods Collaboration, 'Survey Futures'.
Selected recent publications:
Roberts, C. and Voorpostel, M. (2023) Combining data collection modes in longitudinal studies.In D. Spini and E. Widmer (Eds.) Withstanding Vulnerability throughout Adult Life. Dynamics of Stressors, Resources, and Reserves. Springer. Chapter 22, pp. 359-373.
Roberts, C., Herzing, J.E., Asensio Manjon, M., Abbet, P. and Gatica-Perez, D. (2022). Response burden and dropout in a probability-based online panel study – a comparison between an app and browser-based design. Journal of Official Statistics, special issue on ‘Respondent Burden’, 38(4): 987–1017. https://doi.org/10.2478/jos-2022-0043
Pekari, N., Lipps, O., Roberts, C., & Lutz, G. (2022). Conditional distributions of frame variables and voting behaviour in probability-based surveys and opt-in panels. Swiss Political Science Review, 00, 1–16. https://doi.org/10.1111/spsr.12539
Roberts, C., Herzing, J.E., Sobrino Piazza, J., Abbet, P. and Gatica-Perez, D. (2022). Data privacy concerns as a source of resistance to participate in surveys using a smartphone app. Journal of Survey Statistics and Methodology, Special Issue on ‘Privacy, Confidentiality, and Disclosure Protection’, 10(3): 518–548. https://doi.org/10.1093/jssam/smac018
Voorpostel, M., Lipps, O., and Roberts, C. (2021). Mixing modes in household panel surveys: Recent developments and new findings. In P.Lynn (Ed.) Advances in Longitudinal Survey Methodology, Wiley. DOI:10.1002/9781119376965.ch9
Voorpostel, M., Roberts, C., and Ghoorbin, M. (2021). Switching to online data collection in a household panel study: effects on post-recruitment drop-out. Survey Methods Insights from the Field. Retrieved from https://surveyinsights.org/?p=15709. DOI:10.13094/SMIF-2021-00004
Roberts, C. Vandenplas, C., and Herzing, J. (2020). A validation of R-indicators as a measure of the risk of bias using data from a non-response follow-up survey. Journal of Official Statistics, 36(3): 675-701. https://doi.org/10.2478/jos-2020-0034
Roberts, C., Sarrasin, O. and Ernst Stähli, M (2020). The relative impact of different sources of measurement non-equivalence in comparative surveys: Examples of item, method and construct bias. Conditional acceptance from Survey Research Methods, special issue on ‘Measurement Invariance: Testing for it and explaining why it is absent’. https://doi.org/10.18148/srm/2020.v14i4.7416
Roberts, C., Gilbert, E., Allum, N., and Eisner, L. (2019). Satisficing in surveys: Results of a systematic review of the literature. Public Opinion Quarterly, 83(3): 598–626. https://doi.org/10.1093/poq/nfz035
Eisner, L., Clémence, A., Roberts, C., Joost, S., and Theler, J.M. (2019). Developing attitude measures based on respondents’ representations of unfamiliar objects: An application to attitudes towards biodiversity. Field Methods, 31(1): 56-75. https://doi.org/10.1177/1525822X18797280
Roberts, C., and Vandenplas, C. (2017). Estimating components of mean-squared error to evaluate the benefits of mixing data collection modes. Journal of Official Statistics, 33(2): 303-334. http://dx.doi.org/10.1515/JOS-2017-0016
Oris, M., Roberts, C., Joye, D., and Ernst Stähli, M. (Eds.) (2016). Surveying human vulnerabilities across the Life Course. Springer ‘Life Course Research and Social Policies’ series. Roberts, C. (2016). Response styles in surveys: understanding their causes and mitigating their impact on data quality.
In C.Wolf, D. Joye, T.W. Smith, and Y-C. Fu (2016). The Sage Handbook of Survey Methodology. London: Sage Publications. https://doi.org/10.4135/9781473957893.n36
Oris, M., Roberts, C., Joye, D., and Ernst Stähli, M. (2016). Surveying human vulnerabilities across the Life Course: Balancing substantive and methodological challenges.
In M. Oris, C. Roberts, D. Joye, and M. Ernst Stähli. (Eds.) Surveying human vulnerabilities across the Life Course. Springer ‘Life Course Research and Social Policies’ series. Chapter 1, pp. 1-25.