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

Anastasios A. Tsiatis

Biometrika, 2002, vol. 89, issue 1, 238-244

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.

Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:89:y:2002:i:1:p:238-244

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