1998•Scandinavian Journal of StatisticsRequires access

Estimating Survival Curves Under Proportional Hazards Model with Covariate Measurement Errors

Fan Hui Kong, Weihua Huang, Xiaoming Li

Open publisher page 9 citations

Abstract

For the Cox proportional hazards model with additive covariate measurement errors, we propose a corrected cumulative baseline hazard estimator that reduces the bias of the na]ve Breslow estimator. We also derive corresponding modified estimators for the hazard functions and the survival functions of individuals with particular covariate values. Using a Monte Carlo technique developed by Lin et al. (1994), we construct confidence bands for such hazard and survival functions.

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What this paper is about

For the Cox proportional hazards model with additive covariate measurement errors, we propose a corrected cumulative baseline hazard estimator that reduces the bias of the na]ve Breslow estimator. We also derive corresponding modified estimators for the hazard functions and the survival functions of individuals with particular covariate values. Using a Monte Carlo technique developed by Lin et al. (1994), we construct confidence bands for such hazard and survival functions.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

For the Cox proportional hazards model with additive covariate measurement errors, we propose a corrected cumulative baseline hazard estimator that reduces the bias of the na]ve Breslow estimator. We also derive corresponding modified estimators for the hazard functions and the survival functions of individuals with particular covariate values. Using a Monte Carlo technique developed by Lin et al. (1994), we construct confidence bands for such hazard and survival functions.

Key concepts: Covariate, Mathematics, Estimator, Proportional hazards model, Statistics, Hazard ratio, Survival analysis, Hazard

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