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The missing censoring indicator model and the smoothed bootstrap

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  • Subramanian, Sundarraman
  • Bean, Derek

Abstract

For right censored data with missing censoring indicators, sub-density function kernel estimators play a significant role for estimating a survival function. Data-driven bandwidths for computing these kernel estimators are proposed. The bandwidths are obtained as minimizers of certain estimates of the mean integrated squared error (MISE). It is shown that the smoothed bootstrap offers a motivation for choosing the proposed MISE estimates for minimization. The efficacy of the proposed procedures is investigated through simulation studies and some illustrations are provided.

Suggested Citation

  • Subramanian, Sundarraman & Bean, Derek, 2008. "The missing censoring indicator model and the smoothed bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 471-476, December.
    • Handle: RePEc:eee:csdana:v:53:y:2008:i:2:p:471-476
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    References listed on IDEAS

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    1. Cao, R., 1993. "Bootstrapping the Mean Integrated Squared Error," Journal of Multivariate Analysis, Elsevier, vol. 45(1), pages 137-160, April.
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    Cited by:

    1. Subramanian, Sundarraman, 2011. "Multiple imputations and the missing censoring indicator model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 105-117, January.

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