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Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse

Author

Listed:
  • Särndal Carl-Erik

    (Statistics Sweden. Sweden)

  • Traat Imbi

    (Institute of Mathematics and Statistics, University of Tartu, Estonia)

  • Lumiste Kaur

    (Questro Analytics Ltd., Tartu, Estonia)

Abstract

Inference in surveys with nonresponse has been studied extensively in the literature with a focus on the estimation phase. Propensity weighting and calibrated weighting are among the adjustment methods used to reduce the nonresponse bias. The data collection phase has come into focus more recently; the literature on adaptive survey design emphasizes representativeness and degree of balance as desirable properties of the response obtained from a probability sample. We take an integrated view where data collection and estimation are considered together. For a chosen auxiliary vector, we define the concepts incidence and inverse incidence and show their properties and relationship. As we show, incidences are used in balancing the response in data collection; the inverse incidences are important for weighting adjustment in the estimation.

Suggested Citation

  • Särndal Carl-Erik & Traat Imbi & Lumiste Kaur, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Statistics Poland, vol. 19(2), pages 183-200, June.
    • Handle: RePEc:vrs:stintr:v:19:y:2018:i:2:p:183-200:n:2
    DOI: 10.21307/stattrans-2018-011
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    References listed on IDEAS

    as
    1. Kott, Phillip S. & Chang, Ted, 2010. "Using Calibration Weighting to Adjust for Nonignorable Unit Nonresponse," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1265-1275.
    2. Ted Chang & Phillip S. Kott, 2008. "Using calibration weighting to adjust for nonresponse under a plausible model," Biometrika, Biometrika Trust, vol. 95(3), pages 555-571.
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    4. Schouten, Barry & Shlomo, Natalie & Skinner, Chris J., 2011. "Indicators for monitoring and improving representativeness of response," LSE Research Online Documents on Economics 39121, London School of Economics and Political Science, LSE Library.
    5. 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.
    6. F. J. Breidt & G. Claeskens & J. D. Opsomer, 2005. "Model-assisted estimation for complex surveys using penalised splines," Biometrika, Biometrika Trust, vol. 92(4), pages 831-846, December.
    7. Barry Schouten & Fannie Cobben & Peter Lundquist & James Wagner, 2016. "Does more balanced survey response imply less non-response bias?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 727-748, June.
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    Full references (including those not matched with items on IDEAS)

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