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Rare-variant association testing for sequencing data with the sequence kernel association test.
Sequencing studies are increasingly being conducted to identify rare variants associated with complex traits. The limited power of classical single-marker association analysis for rare variants posesExpand
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On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data.
For modern evidence-based medicine, a well thought-out risk scoring system for predicting the occurrence of a clinical event plays an important role in selecting prevention and treatment strategies.Expand
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Joint Effects of Common Genetic Variants on the Risk for Type 2 Diabetes in U.S. Men and Women of European Ancestry
Context Individual genetic polymorphisms are weakly associated with type 2 diabetes. It is unclear whether genetic information adds usefully to the assessment of diabetes risk using only conventionalExpand
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A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data.
TLDR
We propose a class of measures for evaluating the incremental values of new markers, which includes the preceding two as special cases. Expand
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Initial evaluation of coronary images from 320-detector row computed tomography
Purpose To evaluate image quality and contrast opacification from coronary images acquired from 320-detector row computed tomography (CT). Patient dose is estimated for prospective and retrospectiveExpand
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Rare Variant Association Testing for Sequencing Data Using the Sequence Kernel Association Test ( SKAT )
*These authors contributed equally to this work. 1 Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA 2 Department of Biostatistics, HarvardExpand
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Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models
Suppose that we are interested in establishing simple but reliable rules for predicting future t-year survivors through censored regression models. In this article we present inference procedures forExpand
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Analysis of randomized comparative clinical trial data for personalized treatment selections.
Suppose that under the conventional randomized clinical trial setting, a new therapy is compared with a standard treatment. In this article, we propose a systematic, 2-stage estimation procedure forExpand
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Semi-parametric estimation of the binormal ROC curve for a continuous diagnostic test.
Not until recently has much attention been given to deriving maximum likelihood methods for estimating the intercept and slope parameters from a binormal ROC curve that assesses the accuracy of aExpand
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Semiparametric regression analysis for doubly censored data
We analyse doubly censored data using semiparametric transformation models. We provide inference procedures for the regression parameters and derive the asymptotic distributions of the proposedExpand
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