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Multilevel modelling of refusal and non-contact in household surveys: evidence from six UK Government surveys

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  • Durrant, Gabriele B.
  • Steele, Fiona

Abstract

We analyse household unit non-response in six major UK Government surveys by using a multilevel multinomial modelling approach. The models are guided by current conceptual frameworks and theories of survey participation. One key feature of the analysis is the investigation of the extent to which effects of household characteristics are survey specific. The analysis is based on the 2001 UK Census Link Study, which is a unique source of data containing an unusually rich set of auxiliary variables. The study contains the response outcome of six surveys, linked to census data and interviewer observations for both respondents and non-respondents.

Suggested Citation

  • Durrant, Gabriele B. & Steele, Fiona, 2009. "Multilevel modelling of refusal and non-contact in household surveys: evidence from six UK Government surveys," LSE Research Online Documents on Economics 50112, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:50112
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    References listed on IDEAS

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    1. Jan Pickery & Geert Loosveldt, 2002. "A Multilevel Multinomial Analysis of Interviewer Effects on Various Components of Unit Nonresponse," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(4), pages 427-437, November.
    2. C. O'Muircheartaigh & P. Campanelli, 1999. "A multilevel exploration of the role of interviewers in survey non‐response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 437-446.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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    Cited by:

    1. Gabriele B. Durrant & Sylke V. Schnepf, 2018. "Which schools and pupils respond to educational achievement surveys?: a focus on the English Programme for International Student Assessment sample," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1057-1075, October.
    2. Walejko Gina & Wagner James, 2018. "A Study of Interviewer Compliance in 2013 and 2014 Census Test Adaptive Designs," Journal of Official Statistics, Sciendo, vol. 34(3), pages 649-670, September.
    3. Wagner James & Olson Kristen, 2018. "An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys," Journal of Official Statistics, Sciendo, vol. 34(1), pages 211-237, March.
    4. Geert Loosveldt & Koen Beullens, 2014. "A Procedure to Assess Interviewer Effects on Nonresponse Bias," SAGE Open, , vol. 4(1), pages 21582440145, February.
    5. Khudnitskaya, Alesia S., 2009. "Microenvironment-specific Effects in the Application Credit Scoring Model," MPRA Paper 23175, University Library of Munich, Germany.
    6. Alireza Rezaee & Mojtaba Ganjali & Ehsan Bahrami Samani, 2022. "Sample selection bias with multiple dependent selection rules: an application to survey data analysis with multilevel nonresponse," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-15, December.
    7. Michele Lalla & Maddalena Cavicchioli, 2020. "Nonresponse and measurement errors in income: matching individual survey data with administrative tax data," Department of Economics 0170, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    8. Roger Tourangeau & J. Michael Brick & Sharon Lohr & Jane Li, 2017. "Adaptive and responsive survey designs: a review and assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 203-223, January.
    9. Mark Amos, 2018. "Interviewer effects on patterns of nonresponse: Evaluating the impact on the reasons for contraceptive nonuse in the Indonesia and the Philippines DHS," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(14), pages 415-430.
    10. Kristen Olson, 2013. "Paradata for Nonresponse Adjustment," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 142-170, January.
    11. Finaba Berete & Johan Van der Heyden & Stefaan Demarest & Rana Charafeddine & Lydia Gisle & Elise Braekman & Jean Tafforeau & Geert Molenberghs, 2019. "Determinants of unit nonresponse in multi-mode data collection: A multilevel analysis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
    12. Rebecca Vassallo & Gabriele Durrant & Peter Smith, 2017. "Separating interviewer and area effects by using a cross-classified multilevel logistic model: simulation findings and implications for survey designs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 531-550, February.
    13. Francisco Perales & Bernard Baffour & Francis Mitrou, 2015. "Ethnic Differences in the Quality of the Interview Process and Implications for Survey Analysis: The Case of Indigenous Australians," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-20, June.
    14. Barbara Felderer & Jannis Kueck & Martin Spindler, 2021. "Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel," Papers 2102.08994, arXiv.org.
    15. Adriana Ana Maria Davidescu & Monica Roman & Vasile Alecsandru Strat & Mihaela Mosora, 2019. "Regional Sustainability, Individual Expectations and Work Motivation: A Multilevel Analysis," Sustainability, MDPI, vol. 11(12), pages 1-23, June.
    16. Plewis Ian & Shlomo Natalie, 2017. "Using Response Propensity Models to Improve the Quality of Response Data in Longitudinal Studies," Journal of Official Statistics, Sciendo, vol. 33(3), pages 753-779, September.

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    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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