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How to Obtain Valid Inference under Unit Nonresponse?

Author

Listed:
  • Boeschoten Laura

    (Tilburg School of Social and Behavioral Sciences, Tilburg University, Warandelaan 2, 5037 AB Tilburg, The Netherlands.)

  • Vink Gerko
  • Hox Joop J.C.M.

    (Department of Methodology&Statistics, Utrecht University, Padualaan 14, 3584 CH Utrecht, The Netherlands.)

Abstract

Weighting methods are commonly used in situations of unit nonresponse with linked register data. However, several arguments in terms of valid inference and practical usability can be made against the use of weighting methods in these situations. Imputation methods such as sample and mass imputation may be suitable alternatives, as they lead to valid inference in situations of item nonresponse and have some practical advantages. In a simulation study, sample and mass imputation were compared to traditional weighting when dealing with unit nonresponse in linked register data. Methods were compared on their bias and coverage in different scenarios. Both, sample and mass imputation, had better coverage than traditional weighting in all scenarios.

Suggested Citation

  • Boeschoten Laura & Vink Gerko & Hox Joop J.C.M., 2017. "How to Obtain Valid Inference under Unit Nonresponse?," Journal of Official Statistics, Sciendo, vol. 33(4), pages 963-978, December.
    • Handle: RePEc:vrs:offsta:v:33:y:2017:i:4:p:963-978:n:6
    DOI: 10.1515/jos-2017-0045
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    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Hanzhi Zhou & Michael R. Elliott & Trviellore E. Raghunathan, 2016. "A two-step semiparametric method to accommodate sampling weights in multiple imputation," Biometrics, The International Biometric Society, vol. 72(1), pages 242-252, March.
    3. Li‐Chun Zhang, 2012. "Topics of statistical theory for register‐based statistics and data integration," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(1), pages 41-63, February.
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