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A new multiple imputation method for bounded missing values

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  • Kwon, Tae Yeon
  • Park, Yousung

Abstract

A proportioned residual draw method is introduced to impute bounded missing values. It is shown that this new regression-based imputation method is least biased and robust for heavy-tailed and skewed error distributions, regardless of number of boundaries and missing mechanisms.

Suggested Citation

  • Kwon, Tae Yeon & Park, Yousung, 2015. "A new multiple imputation method for bounded missing values," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 204-209.
    • Handle: RePEc:eee:stapro:v:107:y:2015:i:c:p:204-209
    DOI: 10.1016/j.spl.2015.08.028
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    References listed on IDEAS

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    1. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    2. Daniel F. Heitjan & Roderick J. A. Little, 1991. "Multiple Imputation for the Fatal Accident Reporting System," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 13-29, March.
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    Cited by:

    1. Urko Aguirre-Larracoechea & Cruz E. Borges, 2021. "Imputation for Repeated Bounded Outcome Data: Statistical and Machine-Learning Approaches," Mathematics, MDPI, vol. 9(17), pages 1-27, August.

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