Bias and variance reduction in nonparametric estimation of time-dependent accuracy measures

Chin Tsang Chiang, Ming Yueh Huang, Shao Hsuan Wang

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

A new nonparametric approach is developed to estimate the time-dependent accuracy measure curves, which are defined on the cumulative cases and dynamic controls, for censored survival data. Based on an estimable survival process, the main intention of this study is to reduce the finite-sample biases of nearest neighbor estimators. The asymptotic variances of some retrospective accuracy measure estimators are further reduced by applying a smoothing technique to the underlying process of a marker. Meanwhile, practically feasible and theoretically valid procedures are proposed for bandwidth selection in the presented estimators. In addition, the proposed methodology can be reasonably extended to accommodate stratified survival data and survival data with multiple markers. As shown in the simulations, our new estimators outperform the nearest neighbor and inverse censoring weighted estimators. Data from the AIDS Clinical Trials Group study 175 and an angiographic coronary artery disease study are also used to illustrate the proposed methodology.

原文???core.languages.en_GB???
頁(從 - 到)5247-5266
頁數20
期刊Statistics in Medicine
35
發行號28
DOIs
出版狀態已出版 - 10 12月 2016

指紋

深入研究「Bias and variance reduction in nonparametric estimation of time-dependent accuracy measures」主題。共同形成了獨特的指紋。

引用此