Survival analysis with error-prone time-varying covariates: a risk set calibration approach.
Survival analysis with error-prone time-varying covariates: a risk set calibration approach.
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DOI：
10.1111/j.1541-0420.2010.01423.x
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发表时间：
2011-03
期刊：
影响因子：
1.9
通讯作者：
Spiegelman D
中科院分区：
文献类型：
--
作者：
Liao X;Zucker DM;Li Y;Spiegelman D
职业、环境和营养流行病学家通常对估计随时间变化的暴露变量（如累积暴露或累积更新平均暴露）与慢性疾病终点（如癌症发病率和死亡率）的预期效应感兴趣。从暴露验证研究中可以明显看出，许多感兴趣的变量的测量存在中度至严重的误差。虽然普通的回归校准方法是近似有效和有效的测量误差校正的相对风险估计的考克斯模型与时间无关的点暴露时，疾病是罕见的，它是不适用于使用随时间变化的曝光。通过重新校准每个风险集内的测量误差模型，提出了一种风险集回归校准方法。提出了一种使用RRC方法的相对风险的偏差校正点估计的算法，然后推导其方差的估计，从而得到三明治估计。重点是适用于主要研究/外部验证研究设计的方法，这些方法在重要应用中出现。在误差模型的几种假设下进行了仿真研究，验证了该方法在有限样本情况下的有效性。该方法应用于哈佛健康专业人员随访研究（HPFS）的饮食和癌症研究。
Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS).
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影响因子：
158.5
作者：
Hunter, DJ;Spiegelman, D;Willett, W
通讯作者：
Willett, W
影响因子：
5.4
作者：
Brauer, M;Hoek, G;Brunekreef, B
通讯作者：
Brunekreef, B
DOI：
10.1111/1467-9868.00317
发表时间：
2001-01-01
影响因子：
5.8
作者：
Xie, SX;Wang, CY;Prentice, RL
通讯作者：
Prentice, RL
影响因子：
5
作者：
ROSNER, B;SPIEGELMAN, D;WILLETT, WC
通讯作者：
WILLETT, WC
DOI：
10.2307/2983065
发表时间：
1993-01-01
影响因子：
2
作者：
RABOUD, J;REID, N;FAREWELL, VT
通讯作者：
FAREWELL, VT