Multiple imputation methods for estimating regression coefficients in the competing risks model with missing cause of failure.

Abstract:

: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.

journal_name

Biometrics

journal_title

Biometrics

authors

Lu K,Tsiatis AA

doi

10.1111/j.0006-341x.2001.01191.x

subject

Has Abstract

pub_date

2001-12-01 00:00:00

pages

1191-7

issue

4

eissn

0006-341X

issn

1541-0420

journal_volume

57

pub_type

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