Estimation and inference for the population attributable risk in the presence of misclassification [0.03%]
混杂因素存在误分类情况下的人群归因风险的估计和推断
Benedict H W Wong,Jooyoung Lee,Donna Spiegelman et al.
Benedict H W Wong et al.
Because it describes the proportion of disease cases that could be prevented if an exposure were entirely eliminated from a target population as a result of an intervention, estimation of the population attributable risk (PAR) has become an...
The identity of two meta-analytic likelihoods and the ignorability of double-zero studies [0.03%]
两种元分析似然性的身份以及双重零研究的可忽略性
Dankmar Böhning,Patarawan Sangnawakij
Dankmar Böhning
In meta-analysis, the conventional two-stage approach computes an effect estimate for each study in the first stage and proceeds with the analysis of effect estimates in the second stage. For counts of events as outcome, the risk ratio is o...
Corrigendum to: Neuroconductor: an R platform for medical imaging analysis [0.03%]
关于神经导体的勘误：医学图像分析的R平台
John Muschelli,Adrian Gherman,Jean-Philippe Fortin et al.
John Muschelli et al.
Published Erratum
Biostatistics (Oxford, England). 2021 Jul 17;22(3):685. DOI:10.1093/biostatistics/kxaa006 2021
RoBoT: a robust Bayesian hypothesis testing method for basket trials [0.03%]
一种稳健的贝叶斯假设检验方法在篮子试验中的应用
Tianjian Zhou,Yuan Ji
Tianjian Zhou
A basket trial in oncology encompasses multiple "baskets" that simultaneously assess one treatment in multiple cancer types or subtypes. It is well-recognized that hierarchical modeling methods, which adaptively borrow strength across baske...
Yan Liu,Christopher S McMahan,Joshua M Tebbs et al.
Yan Liu et al.
In screening applications involving low-prevalence diseases, pooling specimens (e.g., urine, blood, swabs, etc.) through group testing can be far more cost effective than testing specimens individually. Estimation is a common goal in such a...
Bias due to Berkson error: issues when using predicted values in place of observed covariates [0.03%]
Berkson误差偏差：使用预测值代替观察到的协变量时出现的问题
Gregory Haber,Joshua Sampson,Barry Graubard
Gregory Haber
Studies often want to test for the association between an unmeasured covariate and an outcome. In the absence of a measurement, the study may substitute values generated from a prediction model. Justification for such methods can be found b...
Regularized Bayesian transfer learning for population-level etiological distributions [0.03%]
正则化贝叶斯迁移学习在病因学分布的群体水平研究中的应用
Abhirup Datta,Jacob Fiksel,Agbessi Amouzou et al.
Abhirup Datta et al.
Computer-coded verbal autopsy (CCVA) algorithms predict cause of death from high-dimensional family questionnaire data (verbal autopsy) of a deceased individual, which are then aggregated to generate national and regional estimates of cause...
Estimating disease onset from change points of markers measured with error [0.03%]
基于误差测量标志物的变点估计病发时间
Unkyung Lee,Raymond J Carroll,Karen Marder et al.
Unkyung Lee et al.
Huntington disease is an autosomal dominant, neurodegenerative disease without clearly identified biomarkers for when motor-onset occurs. Current standards to determine motor-onset rely on a clinician's subjective judgment that a patient's ...
Observational Study
Biostatistics (Oxford, England). 2021 Oct 13;22(4):819-835. DOI:10.1093/biostatistics/kxz068 2021
Simultaneous monitoring for regression coefficients and baseline hazard profile in Cox modeling of time-to-event data [0.03%]
Cox模型中同时监测回归系数和基线风险轮廓以分析时间到事件数据
Yishu Xue,Jun Yan,Elizabeth D Schifano
Yishu Xue
The Cox model is the most popular tool for analyzing time-to-event data. The nonparametric baseline hazard function can be as important as the regression coefficients in practice, especially when prediction is needed. In the context of stoc...
Ales Kotalik,David M Vock,Eric C Donny et al.
Ales Kotalik et al.
A number of statistical approaches have been proposed for incorporating supplemental information in randomized clinical trials. Existing methods often compare the marginal treatment effects to evaluate the degree of consistency between sour...