Non-parametric Estimation of a Survival Function with Two-stage Design Studies.
Non-parametric Estimation of a Survival Function with Two-stage Design Studies.
复制标题
两阶段设计研究的生存函数的非参数估计。
DOI：
10.1111/j.1467-9469.2007.00581.x
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Tseng,Chi-Hong
中科院分区：
文献类型：
--
作者：
Li,Gang;Tseng,Chi-Hong
由于其成本效益，两阶段设计在流行病学研究和临床试验中很受欢迎。通常，第一阶段样本包含便宜且可能有偏差的信息，而第二阶段验证样本由具有准确和完整信息的受试者子集组成。在本文中，我们研究了用两阶段设计的右截尾生存数据估计生存函数。结合两个阶段的数据，得到一个非参数估计量。我们还研究了它的大样本性质，并推导了生存函数的点态和同步置信区间。所提出的估计量有效地减少了仅基于第二阶段验证样本的Kaplan-Meier估计量的方差和有限样本偏差。最后，我们将我们的方法应用于医疗器械上市后监测研究的真实数据集。
The two‐stage design is popular in epidemiology studies and clinical trials due to its cost effectiveness. Typically, the first stage sample contains cheaper and possibly biased information, while the second stage validation sample consists of a subset of subjects with accurate and complete information. In this paper, we study estimation of a survival function with right‐censored survival data from a two‐stage design. A non‐parametric estimator is derived by combining data from both stages. We also study its large sample properties and derive pointwise and simultaneous confidence intervals for the survival function. The proposed estimator effectively reduces the variance and finite‐sample bias of the Kaplan–Meier estimator solely based on the second stage validation sample. Finally, we apply our method to a real data set from a medical device postmarketing surveillance study.