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Alternative approaches to multilevel modelling of survey non-contact and refusal

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  • Steele, Fiona
  • Durrant, Gabriele B.

Abstract

We review three alternative approaches to modelling survey non-contact and refusal: multinomial, sequential, and sample selection (bivariate probit) models. We then propose a multilevel extension of the sample selection model to allow for both interviewer effects and dependency between non-contact and refusal rates at the household and interviewer level. All methods are applied and compared in an analysis of household non-response in the United Kingdom, using a data set with unusually rich information on both respondents and non-respondents from six major surveys. After controlling for household characteristics, there is little evidence of residual correlation between the unobserved characteristics affecting non-contact and refusal propensities at either the household or the interviewer level. We also find that the estimated coefficients of the multinomial and sequential models are surprisingly similar, which further investigation via a simulation study suggests is due to non-contact and refusal having largely different predictors.

Suggested Citation

  • Steele, Fiona & Durrant, Gabriele B., 2011. "Alternative approaches to multilevel modelling of survey non-contact and refusal," LSE Research Online Documents on Economics 50113, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:50113
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    References listed on IDEAS

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    1. Gabriele B. Durrant & Julia D'Arrigo & Fiona Steele, 2011. "Using paradata to predict best times of contact, conditioning on household and interviewer influences," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 1029-1049, October.
    2. Cheti Nicoletti & Franco Peracchi, 2005. "Survey response and survey characteristics: microlevel evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 763-781, November.
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    4. Gabriele B. Durrant & Fiona Steele, 2009. "Multilevel modelling of refusal and non‐contact in household surveys: evidence from six UK Government surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 361-381, April.
    5. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
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    8. Fiona Steele & Constantinos Kallis & Heather Joshi, 2006. "The formation and outcomes of cohabiting and marital partnerships in early adulthood: the role of previous partnership experience," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 757-779, October.
    9. Denise Hawkes & Ian Plewis, 2006. "Modelling non‐response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491, July.
    10. Durrant, Gabriele B. & D'Arrigo, Julia & Steele, Fiona, 2011. "Using field process data to predict best times of contact conditioning on household and interviewer influences," LSE Research Online Documents on Economics 52201, London School of Economics and Political Science, LSE Library.
    11. Lynn, Peter & S. Clarke, Paul, 2001. "Separating refusal bias and non-contact bias: evidence from UK national surveys," ISER Working Paper Series 2001-24, Institute for Social and Economic Research.
    12. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    13. F. C. Billari & R. Borgoni, 2005. "Assessing the use of sample selection models in the estimation of fertility postponement effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(3), pages 389-402, December.
    14. 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.
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    Cited by:

    1. Jamie C. Moore & Gabriele B. Durrant & Peter W. F. Smith, 2021. "Do coefficients of variation of response propensities approximate non‐response biases during survey data collection?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 301-323, January.
    2. 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.
    3. Brick J. Michael, 2013. "Unit Nonresponse and Weighting Adjustments: A Critical Review," Journal of Official Statistics, Sciendo, vol. 29(3), pages 329-353, June.

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

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