Journal
BIOMETRICS
Volume 57, Issue 4, Pages 1191-1197Publisher
INTERNATIONAL BIOMETRIC SOC
DOI: 10.1111/j.0006-341X.2001.01191.x
Keywords
cause-specific hazard; missing at random; partial likelihood
Funding
- NCI NIH HHS [CA-51962] Funding Source: Medline
- NIAID NIH HHS [AI-31789] Funding Source: Medline
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We propose a method to estimate the regression coefficients in a competing risks model where the cause-specific hazard for the cause of interest is related to covariates through a proportional hazards relationship and when cause of failure is missing for some individuals. We use multiple imputation procedures to impute missing cause of failure, where the probability that a missing cause is the cause of interest may depend on auxiliary covariates, and combine the maximum partial likelihood estimators computed from several imputed data sets into an estimator that is consistent and asymptotically normal. A consistent estimator for the asymptotic variance is also derived. Simulation results suggest the relevance of the theory in finite samples. Results are also illustrated with data from a breast cancer study.
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