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Welcome to the Centre for Comparative Social Surveys.
The Centre for Comparative Social Surveys (CCSS) was established in 2003 and has since built a team of experts specialising in the design, implementation, and analysis of large scale and cross-national surveys. In addition, the CCSS experts engage in research on linking other data sources, e.g., administrative and geographical data to surveys. This includes technical solutions to anonymisation, micro simulations, and automatic coding.
The CCSS experts engage in research on linking other data sources, e.g., administrative and geographical data to surveys. This includes technical solutions to anonymisation, micro simulations, and automatic coding. The CCSS host a variety of externally funded research projects investigating methodological and substantive issues in large scale and comparative surveys.
Among these projects are:
Professor Rainer Schnell
Find out more about the people who are part of the Centre for Comparative Social Surveys
Mary Keane, Administrator
Claire Harding, Administrator
Dr Sarah Butt
The Centre for Comparative Social Surveys (CCSS) is the headquarters of the European Social Survey (ESS), an academically driven cross-national survey of public attitudes and opinions carried out in more than 30 European countries.
Since 2013 the ESS has been established as a European Research Infrastructure Consortium (ERIC), cementing its place at the heart of European social science.
Carried out every two years, the survey provides rigorous cross-national data on a wide range of topics including:
Data from ESS Rounds 1-7 are freely available to download via the project website.
CCSS staff are involved in all aspects of ESS survey design and implementation, helping to ensure that the survey is conducted to the highest methodological standards and remains at the forefront of comparative survey research. Preparations are well underway for Round 8 of the survey which will enter the field in September 2016. ESS Round 8 will include modules of questions on attitudes to welfare provision and energy use and climate change. A call for rotating module topics for ESS Round 9 (2018/19) has been issued.
Data from Round 7 of the survey (2014/15) are now available to download from the ESS website.
ESS ERIC is coordinating a major social science cluster project. Funded by the European Commission under its Horizon 2020 programme, the €8.4m SERISS project (which runs until June 2019) aims to ensure that Europe’s social science data infrastructures are able to play an effective role in addressing the key challenges facing Europe today, as well as equipping national and European policy makers with a solid base of the highest-quality evidence on people’s attitudes, experiences and behaviour.
The ESS is working together with the Survey for Health Aging and Retirement in Europe (SHARE), the Consortium of European Social Science Data Archives (CESSDA), the Generations and Gender Programme (GGP), European Values Study (EVS) and the WageIndicator Survey to address some of the key challenges facing cross-national data collection, break down barriers between research infrastructures and embrace the future of social science via new forms of data collection.
The ESS ERIC has secured a €2.3 million grant from the European Commission to help it increase the number of countries that take part in its research. It is hoped that a significant increase in ESS membership will translate into lower costs of participation for the nations involved, while also strengthening the power of the survey’s datasets, and thus help to sustain the survey infrastructure.
ESS-SUSTAIN has the following key aims:
The grant will support a number of activities including an impact case study in member countries, the appointment of ESS ambassadors to promote the study, investigation about accessing structural funds to finance membership and enhanced communications to highlight the output arising from the survey.
Rory Fitzgerald, Sarah Butt and Kaisa Lahtinen are involved in an ESRC-funded research project investigating the potential of auxiliary data to understand and correct for non-response bias in Round 6 of the ESS in the UK.
Find out more about ADDResponse.
Eric Harrison is working with colleagues from the New Economics Foundation and Cambridge University on an ESRC-funded project to build sustained public and political interest in the use of well-being data, and to explore where policy recommendations based on well-being data are possible. The project uses ESS data on subjective wellbeing including items from the core questionnaire and the Round 3 and Round 6 rotating modules on Personal and Social Wellbeing.
Find out more about the Making Wellbeing Count for Policy project.
For further details of publications by Centre for Comparative Social Survey staff please see their individual academic profiles.
The Centre for Comparative Social Surveys is home to the headquarters of the European Social Survey (ESS).
There are a number of publications available that provide further information about the survey and contain analysis of the data.
In 2011, we launched a new series of ESS Topline Findings, which are concise cross-national summaries of particular topics covered in the questionnaire. Number 1 in the series focuses on trust in justice using data from Round 5 of the survey. Number 2 focuses on welfare attitudes in Europe using data from Round 4 of the survey. Number 3 focuses on the economic crisis, quality of work and social integration using data from Rounds 2 and 5 of the ESS. Number 4 focuses on Europeans' understandings and evaluations of democracy using data from Round 6 of the ESS and Number 5 focuses on dimensions of personal and social wellbeing, also using data from Round 6 of the survey.
This is a selection of key findings, both published and unpublished, using data from the first five rounds of the survey. This was released in July 2013.
A website and accompanying publication bringing together new research on the topic of subjective wellbeing by leading academic and policy experts using ESS data.
The Centre also produces working papers on topics related to its ongoing programme of methodological research.
Winstone, L., Widdop, S. & Fitzgerald, R. (2016). Constructing the Questionnaire: the Challenges of Measuring Views and Evaluations of Democracy Across Europe. In: M. Ferrin & H. Kriesi (Eds.), How Europeans View and Evaluate Democracy (Comparative Politics). (pp. 21-42). UK: Oxford University Press. ISBN 978-0-19-876690-2
Blom, A. G., Bosnjak, M., Cornilleau, A., Cousteaux, A. S., Das, M., Douhou, S. & Krieger, U. (2016). A Comparison of Four Probability-Based Online and Mixed-Mode Panels in Europe. Social Science Computer Review, 34(1), pp. 8-25. doi: 10.1177/0894439315574825
Kroll, M. & Schnell, R. (2016). Anonymisation of geographical distance matrices via Lipschitz embedding. International Journal of Health Geographics, 15(1), doi: 10.1186/s12942-015-0031-7
Fitzgerald, R. (2015). Striving for quality, comparability and transparency in cross-national social survey measurement: illustrations from the European Social Survey (ESS). (Unpublished Doctoral thesis, City University London)
Reece Thomas, K. (2015). Enforcing against state assets:the case for restricting private creditor enforcement and how judges in England have used "context" when applying the "commercial purposes" test. Journal of International and Comparative Law, 2(1),
Geurs, K. T., Thomas, T., Bijlsma, M. & Douhou, S. (2015). Automatic trip and mode detection with move smarter: First results from the Dutch Mobile Mobility Panel. Transportation Research Procedia, 11, pp. 247-262. doi: 10.1016/j.trpro.2015.12.022
Lahtinen, K., Slingsby, A., Dykes, J., Butt, S. & Fitzgerald, R. (2015). Informing Non-Response Bias Model Creation in Social Surveys with Visualisation. Paper presented at the VIS 2015, 25-10-2015 - 30-10-2015, Chicago, USA.
Schnell, R. & Borgs, C. (2015). Building a national perinatal database without the use of unique personal identifiers. Paper presented at the IEEE International Conference on Data Mining, 14-11-2015 - 17-11-2015, Atlantic City, USA.
Niedermeyer, F., Steinmetzer, S., Kroll, M. & Schnell, R. (2014). Cryptanalysis of Basic Bloom Filters Used for Privacy Preserving Record Linkage. Journal of Privacy and Condentiality, 6(2), pp. 59-79.
Fitzgerald, R., Winstone, L. & Prestage, Y (2014). A Versatile tool? Applying the Cross-national Error Source Typology (CNEST) to triangulated pre-test data. Lausanne: FORS.
Braghiroli, S. & Salini, L. (2014). How Do the Others See Us? An Analysis of Public Opinion Perceptions of the EU and USA in Third Countries. Transworld(33), pp. 1-19.
Callegaro, M., Villar, A., Krosnick, J. & Yeager, D. (2014). A Critical Review of Studies Investigating the Quality of Data Obtained With Online Panels. In: M. Callegaro, R. Baker, J. Bethlehem, A. Goritz, J. Krosnick & P. Lavrakas (Eds.), Online Panel Research: A Data Quality Perspective. (pp. 23-53). UK: John Wiley & Sons. ISBN 978-1-119-94177-4
Schoua-Glusberg, A. & Villar, A. (2014). Assessing Translated Questions via Cognitive Testing. In: K. Miller, S. Willson, V. Chepp & J. L. Padilla (Eds.), Cognitive Interviewing Methodology. (pp. 51-67). Hoboken, USA: John Wiley & Sons. ISBN 9781118383544
Fitzgerald, R., Winstone, L. & Prestage, Y. (2014). Searching For Evidence of Acculturation: Attitudes Toward Homosexuality Among Migrants Moving From Eastern to Western Europe. International Journal of Public Opinion Research, 26(3), pp. 323-341. doi: 10.1093/ijpor/edu021
Schnell, R. (2014). The Accuracy of Pre-Election Polling of German General Elections. MDA - Methods, Data, Analysis, 8(1), pp. 5-24. doi: 10.12758/mda.2014.001
Schnell, R. (2014). An efficient Privacy-Preserving Record Linkage Technique for Administrative Data and Censuses. Statistical Journal of the IAOS, 30(3), pp. 263-270. doi: 10.3233/SJI-140833
Schnell, R., Trappmann, M. & Gramlich, T. (2014). A Study of Assimilation Bias in Name-Based Sampling of Migrants. Journal of Official Statistics, 30(2), pp. 231-249. doi: 10.2478/jos-2014-0015
Villar, A., Callegaro, M. & Yang, Y. (2013). Where Am I? A Meta-Analysis of Experiments on the Effects of Progress Indicators for Web Surveys. Social Science Computer Review, 31(6), pp. 744-762. doi: 10.1177/0894439313497468
Ryan, L., Cooper, P. & Drey, N. (2013). University Research Ethics Committees as learning communities: Identifying and utilising collaboratively produced knowledge in decision-making. Research Ethics, 9(4), pp. 166-174. doi: 10.1177/1747016112437688
Schnell, R. (2013). Efficient private record linkage of very large datasets. Paper presented at the 59th World Statistics Congress of the International Statistical Institute, 25-30 Aug 2013, Hong Kong.
Schnell, R. (2013). Privacy-Preserving Record Linkage and Privacy-Preserving Blocking for Large Files with Cryptographic Keys using Multibit Trees. Paper presented at the Joint Statistical Meeting, 3-8 Aug 2013, Montreal, Canada.
Schnell, R., Gramlich, T., Bachteler, T., Reiher, J., Trappmann, M., Smid, M. & Becher, I. (2013). Ein neues Verfahren für namensbasierte Zufallsstichproben von Migranten. MDA - Methoden, Daten, Analysen, 7(1), pp. 5-33. doi: 10.12758/mda.2013.001
Ryan, L. (2012). "You must be very intelligent...?": Gender and Science Subject Uptake. International Journal of Gender, Science and Technology, 4(2), pp. 167-190.
Jackson, J., Bradford, B., Hough, M., Kuha, J., Stares, S., Widdop, S., Fitzgerald, R., Yordanova, M. & Galev, T. (2011). Developing European indicators of trust in justice. European Journal of Criminology, 8(4), pp. 267-285. doi: 10.1177/1477370811411458
Fitzgerald, R., Widdop, S., Gray, M. & Collins, D. (2011). Identifying sources of error in cross-national questionnaires: Application of an error source typology to cognitive interview data. Journal of Official Statistics, 27(4), pp. 569-599.
Barnes, M., Butt, S. & Tomaszewski, W. (2010). The Duration of Bad Housing and Living Standards of Children in Britain. Housing Studies, 26(1), pp. 155-176. doi: 10.1080/02673037.2010.512749
Broom, M., Crowe, M. L., Fitzgerald, M. R. & Rychtar, J. (2010). The stochastic modelling of kleptoparasitism using a Markov process. Journal of Theoretical Biology, 264(2), pp. 266-272. doi: 10.1016/j.jtbi.2010.01.012
Low, N., Butt, S., Ellis, P. & Davis Smith, J. (2007). Helping out: a national survey of volunteering and charitable giving. London: Cabinet Office.
Butt, S. & Lahtinen, K. Using auxiliary data to model nonresponse bias The challenge of knowing too much about nonrespondents rather than too little?. Paper presented at the International Workshop on Household Nonresponse 2015, 02 Sep 2015 - 04 Sep 2015, Leuven, Belgium.
Butt, S., Lahtinen, K. & Brunsdon, C. Using geographically weighted regression to explore spatial variation in survey data. Paper presented at the GISRUK 2016, 30th March - 1st April 2016, London, UK.
Eikemo, T., Bambra, C., Huijts, T. & Fitzgerald, R. The first pan-European sociological health inequalities survey of the general population: the European Social Survey (ESS) rotating module on the social determinants of health. European Sociological Review,
Harrison, EK & Smart, A The under-representation of minority ethnic groups in UK medical research. Ethnicity and Health, doi: 10.1080/13557858.2016.1182126
Turkay, C., Slingsby, A., Lahtinen, K., Butt, S. & Dykes, J. Enhancing a Social Science Model-building Workflow with Interactive Visualisation. Paper presented at the The European Symposium on Artificial Neural Networks (ESANN 2016), 27-29 Apr 2016, Bruges, Belgium.
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