Estimation of the Conditional Survival Function under Nested Case Control Studies
Date Issued
2014
Date
2014
Author(s)
Li, Yu-Zheng
Abstract
Under random censorship, the Kaplan-Meier type estimator of Beran(1981) has been wildly used to detect the relationship between event time and covariates of interest. However, there is still no automatic selection procedure for bandwidth selection. In cohort study, some covariates might be expansive in collection. Thus, the nested case control study is an alternative avenue to reduce the cost of cohort studies. Whereas the covariates of some subjects will be missing. In this article, the Beran estimator was shown as a solution of our developed estimating equation. In terms of the estimating equation, the sampling bias can be solved by using the inverse probability weighted approach. Meanwhile, the two-step bandwidth selection procedure is developed the estimate the optimal bandwidth of the Kaplan-Meier type survival estimator. In addition, the random weighted estimator is employed to approximate the asymptotic variance of the resulting estimator. In the simulation studies, the performance of bandwidth selection and variance estimation are quite well for finite-samples.
Subjects
條件存活函數
帶寬選擇
逆機率加權法
估計方程式
隨機加權估計式
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-103-R00221017-1.pdf
Size
23.54 KB
Format
Adobe PDF
Checksum
(MD5):ed5efa93d4cee955076606ebbfb5c904