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Multiple imputation methods for testing treatment differences in survival distributions with missing cause of failure

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  • Anastasios A. Tsiatis

Abstract

We propose a method for comparing survival distributions when cause-of-failure information is missing for some individuals. We use multiple imputation to impute missing causes of failure, where the probability that a missing cause is that of interest may depend on auxiliary covariates, and combine log-rank statistics computed from several 'completed' datasets into a test statistic that achieves asymptotically the nominal level. Simulations demonstrate the relevance of the theory in finite samples. Copyright Biometrika Trust 2002, Oxford University Press.

Suggested Citation

  • Anastasios A. Tsiatis, 2002. "Multiple imputation methods for testing treatment differences in survival distributions with missing cause of failure," Biometrika, Biometrika Trust, vol. 89(1), pages 238-244, March.
    • Handle: RePEc:oup:biomet:v:89:y:2002:i:1:p:238-244
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    Cited by:

    1. Wang, Qihua & Liu, Wei & Liu, Chunling, 2009. "Probability density estimation for survival data with censoring indicators missing at random," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 835-850, May.
    2. Subramanian, Sundarraman, 2011. "Multiple imputations and the missing censoring indicator model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 105-117, January.
    3. Bandyopadhyay, Dipankar & Jácome, M. Amalia, 2016. "Comparing conditional survival functions with missing population marks in a competing risks model," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 150-160.
    4. Qihua Wang & Gregg Dinse & Chunling Liu, 2012. "Hazard function estimation with cause-of-death data missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 415-438, April.
    5. Subramanian, Sundarraman, 2009. "The multiple imputations based Kaplan-Meier estimator," Statistics & Probability Letters, Elsevier, vol. 79(18), pages 1906-1914, September.
    6. Mondal, Shoubhik & Subramanian, Sundarraman, 2014. "Model assisted Cox regression," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 281-303.
    7. Subramanian, Sundarraman, 2016. "Bootstrap likelihood ratio confidence bands for survival functions under random censorship and its semiparametric extension," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 58-81.

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