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Estimation and confidence bands of a conditional survival function with censoring indicators missing at random

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  • Wang, Qihua
  • Shen, Junshan

Abstract

The nonparametric estimator of the conditional survival function proposed by Beran is a useful tool to evaluate the effects of covariates in the presence of random right censoring. However, censoring indicators of right censored data may be missing for different reasons in many applications. We propose some estimators of the conditional cumulative hazard and survival functions which allow to handle this situation. We also construct the likelihood ratio confidence bands for them and obtain their asymptotic properties. Simulation studies are used to evaluate the performances of the estimators and their confidence bands.

Suggested Citation

  • Wang, Qihua & Shen, Junshan, 2008. "Estimation and confidence bands of a conditional survival function with censoring indicators missing at random," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 928-948, May.
    • Handle: RePEc:eee:jmvana:v:99:y:2008:i:5:p:928-948
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    References listed on IDEAS

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    1. Li, Gang, 1995. "On nonparametric likelihood ratio estimation of survival probabilities for censored data," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 95-104, November.
    2. Lo, Shaw-Hwa, 1991. "Estimating a survival function with incomplete cause-of-death data," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 217-235, November.
    3. Gang Li & Ingrid Van Keilegom, 2002. "Likelihood Ratio Confidence Bands in Non–parametric Regression with Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(3), pages 547-562, September.
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    Cited by:

    1. Xiaoshuang Zhou & Peixin Zhao, 2022. "Estimation and inferences for varying coefficient partially nonlinear quantile models with censoring indicators missing at random," Computational Statistics, Springer, vol. 37(4), pages 1727-1750, September.
    2. Ali Al-Sharadqah & Majid Mojirsheibani, 2020. "A simple approach to construct confidence bands for a regression function with incomplete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 81-99, March.
    3. Shen, Yu & Liang, Han-Ying, 2018. "Quantile regression for partially linear varying-coefficient model with censoring indicators missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 1-18.

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