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Bayesian Bootstrap in Multiple Frames

Author

Listed:
  • Daniela Cocchi

    (Department of Statistical Sciences, University of Bologna, 40126 Bologna, Italy)

  • Lorenzo Marchi

    (KU Leuven, Research Centre Insurance, 3000 Leuven, Belgium)

  • Riccardo Ievoli

    (Department of Chemical, Pharmaceutical and Agricultural Sciences University of Ferrara, 44121 Ferrara, Italy)

Abstract

Multiple frames are becoming increasingly relevant due to the spread of surveys conducted via registers. In this regard, estimators of population quantities have been proposed, including the multiplicity estimator. In all cases, variance estimation still remains a matter of debate. This paper explores the potential of Bayesian bootstrap techniques for computing such estimators. The suitability of the method, which is compared to the existing frequentist bootstrap, is shown by conducting a small-scale simulation study and a case study.

Suggested Citation

  • Daniela Cocchi & Lorenzo Marchi & Riccardo Ievoli, 2022. "Bayesian Bootstrap in Multiple Frames," Stats, MDPI, vol. 5(2), pages 1-11, June.
    • Handle: RePEc:gam:jstats:v:5:y:2022:i:2:p:34-571:d:839811
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    References listed on IDEAS

    as
    1. I. Sánchez-Borrego & A. Arcos & M. Rueda, 2019. "Kernel-based methods for combining information of several frame surveys," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(1), pages 71-86, January.
    2. Maria del Mar Rueda & Antonio Arcos & David Molina & Maria Giovanna Ranalli, 2018. "Estimation Techniques for Ordinal Data in Multiple Frame Surveys with Complex Sampling Designs," International Statistical Review, International Statistical Institute, vol. 86(1), pages 51-67, April.
    3. Lohr, Sharon & Rao, J.N.K., 2006. "Estimation in Multiple-Frame Surveys," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1019-1030, September.
    4. Maria Mar Rueda & Maria Giovanna Ranalli & Antonio Arcos & David Molina, 2021. "Population empirical likelihood estimation in dual frame surveys," Statistical Papers, Springer, vol. 62(5), pages 2473-2490, October.
    5. Rao, J. N. K. & Wu, Changbao, 2010. "Pseudo–Empirical Likelihood Inference for Multiple Frame Surveys," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1494-1503.
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