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Methods for variance estimation under random hot deck imputation in business surveys

Author

Listed:
  • Paolo Righi

    (Italian National Institute of Statistics)

  • Stefano Falorsi

    (Italian National Institute of Statistics)

  • Andrea Fasulo

    (Italian National Institute of Statistics)

Abstract

When the imputed values are treated as if they were observed the precision of the estimates is generally overstated. In the paper three variance methods under imputatation are taken into account. Two of them are the well known bootstrap and Multiple Imputation. The third is a new method based on grouped jackknife easy to implement, not computer intensive and suitable when random hot deck imputation is performed. A simulative comparison on real business data has been carried out. The findings show that the proposed method has good performances with respect to the other ones.

Suggested Citation

  • Paolo Righi & Stefano Falorsi & Andrea Fasulo, 2014. "Methods for variance estimation under random hot deck imputation in business surveys," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 16(1-2), pages 45-64.
  • Handle: RePEc:isa:journl:v:16:y:2011:i:1-2:p:45-64
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    File URL: http://www.istat.it/it/files/2014/10/Articolo-4_Methodos-for-variance....pdf
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    References listed on IDEAS

    as
    1. Saigo, H. & Sitter, R.R., 2005. "Jackknife variance estimator with reimputation for randomly imputed survey data," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 321-331, July.
    2. Jae Kwang Kim, 2004. "Fractional hot deck imputation," Biometrika, Biometrika Trust, vol. 91(3), pages 559-578, September.
    3. Jae Kwang Kim & J. Michael Brick & Wayne A. Fuller & Graham Kalton, 2006. "On the bias of the multiple‐imputation variance estimator in survey sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 509-521, June.
    4. Kott, Phillip S., 2001. "Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys," NASS Research Reports 235089, United States Department of Agriculture, National Agricultural Statistics Service.
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    Cited by:

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    More about this item

    Keywords

    Bootstrap; Multiple Imputation; Jacknife; Extended DAGJK; Replicate weights; Monte Carlo simulation.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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