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Bayesian Semi-Parametric Regression for Quantile Residual Lifetime
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 Title & Authors
Bayesian Semi-Parametric Regression for Quantile Residual Lifetime
Park, Taeyoung; Bae, Wonho;
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The quantile residual life function has been effectively used to interpret results from the analysis of the proportional hazards model for censored survival data; however, the quantile residual life function is not always estimable with currently available semi-parametric regression methods in the presence of heavy censoring. A parametric regression approach may circumvent the difficulty of heavy censoring, but parametric assumptions on a baseline hazard function can cause a potential bias. This article proposes a Bayesian semi-parametric regression approach for inference on an unknown baseline hazard function while adjusting for available covariates. We consider a model-based approach but the proposed method does not suffer from strong parametric assumptions, enjoying a closed-form specification of the parametric regression approach without sacrificing the flexibility of the semi-parametric regression approach. The proposed method is applied to simulated data and heavily censored survival data to estimate various quantile residual lifetimes and adjust for important prognostic factors.
Bayesian nonparametrics;heavy censoring;median residual lifetime function;partial collapse;survival analysis;
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비대칭적 점프확산 모형의 효율적인 베이지안 추론,박태영;이영은;

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