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Biometrika 2002 89(1):238-244; doi:10.1093/biomet/89.1.238
© 2002 by Biometrika Trust
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Miscellaneous

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

Anastasios A.Tsiatis1, Marie Davidian1 and Brad McNeney2

1 Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, U.S.Atsiatis{at}stat.ncsu.edu davidian{at}stat.ncsu.edu 2 Department of Mathematics and Statistics, Simon Fraser University, Burnaby, British Colombia VSA 1S6, Canada mcneney{at}stat.sfu.ca

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.

Key Words: Competing risks; Log-rank test; Missing at random; Survival analysis


Received August 2000. Revised August 2001


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