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    题名: Bias and variance reduction in nonparametric estimation of time-dependent accuracy measures
    作者: 王紹宣;Chiang, Chin-Tsang;Huang, Ming-Yueh;Wang, Shao-Hsuan
    贡献者: 理學院統計研究所
    关键词: Accuracy;bandwidth selection;Bias;Biomarkers;Computer Simulation;conditional survival function;Coronary Artery Disease - diagnosis;Estimating techniques;Gaussian process;Humans;kernel function;marker-dependent censoring;positive/negative predictive value;receiver operating characteristic curve;Reproducibility of Results;Retrospective Studies;Simulation;Survival analysis;Time;true/false positive rate;U-statistic
    日期: 2016-12-10
    上传时间: 2026-04-23 12:52:22 (UTC+8)
    出版者: John Wiley and Sons Ltd;England: Blackwell Publishing Ltd
    摘要: 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. Copyright © 2016 John Wiley & Sons, Ltd.
    其他題名: Statist. Med
    出版者: England: Blackwell Publishing Ltd
    出版日期: 2016-12-10
    出處: Statistics in medicine, 2016-12, Vol.35 (28), p.5247-5266
    資源來源: Wiley Online Library - AutoHoldings Journals
    版權: Copyright © 2016 John Wiley & Sons, Ltd.
    版權: Copyright Wiley Subscription Services, Inc. Dec 10, 2016
    識別號: ISSN: 0277-6715
    識別號: ISSN: 1097-0258
    識別號: EISSN: 1097-0258
    識別號: DOI: 10.1002/sim.7058
    識別號: PMID: 27439986
    識別號: CODEN: SMEDDA
    显示于类别:[統計研究所] 期刊論文

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