Bayesian analysis of survival data with missing censoring indicators.
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ABSTRACT:
SUBMITTER: Brownstein NC
PROVIDER: S-EPMC7733523 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
Bayesian analysis of survival data with missing censoring indicators.
Brownstein Naomi C NC Bunn Veronica V Castro Luis M LM Sinha Debajyoti D
Biometrics 20200504 1
In some large clinical studies, it may be impractical to perform the physical examination to every subject at his/her last monitoring time in order to diagnose the occurrence of the event of interest. This gives rise to survival data with missing censoring indicators where the probability of missing may depend on time of last monitoring and some covariates. We present a fully Bayesian semi-parametric method for such survival data to estimate regression parameters of the proportional hazards mode ...[more]
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