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Semiparametric estimation of quality adjusted lifetime distribution in semi-Markov illness-death model

机译:半马尔可夫病死模型中质量调整的寿命分布的半参数估计

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In this work, we consider semiparametric estimation of quality adjusted lifetime (QAL) distribution using Cox proportional hazards model for the sojourn time in each health state. The regression coefficients are estimated by maximizing the corresponding partial likelihood and the baseline cumulative hazards are estimated by using the method of Breslow (Biometrics 30:89-99, 1974). The estimate of QAL distribution is obtained by using these estimates in the theoretical expression of QAL distribution. The asymptotic normality of the proposed estimator is established. The performance of the proposed estimator is studied using Monte Carlo simulation. Areal data example of the Stanford Heart Transplant Program is used to illustrate the proposed method. Extension to a general model is also discussed and illustrated with an analysis of International Breast Cancer Study Group (IBCSG) Trial V data.
机译:在这项工作中,我们考虑使用Cox比例风险模型对每种健康状态下的逗留时间进行质量调整寿命(QAL)分布的半参数估计。通过使相应的部分可能性最大化来估计回归系数,并使用Breslow方法(Biometrics 30:89-99,1974)来估计基线累积危害。通过在QAL分布的理论表达式中使用这些估计来获得QAL分布的估计。建立了所提出估计量的渐近正态性。使用蒙特卡洛模拟研究了提出的估计器的性能。斯坦福心脏移植计划的地区数据示例用于说明该方法。还通过对国际乳腺癌研究小组(IBCSG)试验V数据的分析来讨论和说明了对通用模型的扩展。

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