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Activity Number:
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404
- Quantile, Semiparametric and Nonparametric Methods in Survival Analysis
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Type:
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Contributed
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Date/Time:
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Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #307059
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Title:
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Estimating Cross Quantile Residual Ratio with Left-Truncated Semi-Competing Risks Data
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Author(s):
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Jing Yang* and Limin Peng
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Companies:
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Merck & Co., Inc and Emory University
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Keywords:
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Left truncation;
Quantile residule time;
Semi-competing risks
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Abstract:
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A semi-competing risks setting often arises in biomedical studies, involving both a nonterminal event and a terminal event. Cross quantile residual ratio (Yang and Peng in Biometrics 72:770–779, 2016) offers a flexible and robust perspective to study the dependency between the nonterminal and the terminal events which can shed useful scientific insight. We propose a new nonparametric estimator of this dependence measure with left truncated semi-competing risks data. The new estimator overcomes the limitation of the existing estimator that is resulted from demanding a strong assumption on the truncation mechanism. We establish the asymptotic properties of the proposed estimator and develop inference procedures accordingly. Simulation studies suggest good finite-sample performance of the proposed method. Our proposal is illustrated via an application to Denmark diabetesregistry data.
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Authors who are presenting talks have a * after their name.
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