...
首页> 外文期刊>Biostatistics >Accelerated failure time models for censored survival data under referral bias
【24h】

Accelerated failure time models for censored survival data under referral bias

机译:推荐偏见下用于审查生存数据的加速故障时间模型

获取原文
获取原文并翻译 | 示例

摘要

The estimation of progression to liver cirrhosis and identifying its risk factors are often of epidemiological interest in hepatitis C natural history study. In most hepatitis C cohort studies, patients were usually recruited to the cohort with a referral bias because clinically the patients with more rapid disease progression were preferentially referred to liver clinics. A pair of correlated event times may be observed for each patient, time to development of cirrhosis and time to referral to a cohort. This paper considers accelerated failure time models to study the effects of covariates on progression to cirrhosis. A new non-parametric estimator is proposed to handle a flexible bivariate distribution of the cirrhosis and referral times and to take the referral bias into account. The asymptotic normality of the proposed estimator is also provided. Numerical studies show that the coefficient estimator and its covariance function estimator perform well.
机译:在丙型肝炎自然史研究中,对肝硬化进展的评估和确定其危险因素通常是流行病学关注的问题。在大多数丙型肝炎队列研究中,由于临床上疾病进展较快的患者优先转诊至肝病门诊,因此通常以转诊偏倚招募该患者。对于每个患者,可以观察到一对相关的事件时间,发展为肝硬化的时间和转诊至队列的时间。本文考虑加速失效时间模型,以研究协变量对肝硬化进展的影响。提出了一种新的非参数估计器来处理肝硬化和转诊时间的灵活的双变量分布,并考虑转诊偏差。还提供了拟议估计量的渐近正态性。数值研究表明,系数估计器及其协方差函数估计器性能良好。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号