Estimating the Causal Effect of Treatment in Observational Studies with Survival Time Endpoints and Unmeasured Confounding [0.03%]
具有未测量的混淆因素和生存时间结果的观察研究中的处理因果效应估计
Jaeun Choi,A James O&#x;Malley
Jaeun Choi
Estimation of the effect of a treatment in the presence of unmeasured confounding is a common objective in observational studies. The Two Stage Least Squares (2SLS) Instrumental Variables (IV) procedure is frequently used but is not applica...
Optimal treatment allocations in space and time for on-line control of an emerging infectious disease [0.03%]
时空最优分配方案以实现新兴传染病在线控制
Eric B Laber,Nick J Meyer,Brian J Reich et al.
Eric B Laber et al.
A key component in controlling the spread of an epidemic is deciding where, when and to whom to apply an intervention. We develop a framework for using data to inform these decisions in realtime. We formalize a treatment allocation strategy...
Yin-Hsiu Chen,Bhramar Mukherjee,Veronica J Berrocal
Yin-Hsiu Chen
Distributed lag models (DLMs) have been widely used in environmental epidemiology to quantify the lagged effects of air pollution on a health outcome of interest such as mortality and morbidity. Most previous DLM approaches only consider on...
Constructing treatment decision rules based on scalar and functional predictors when moderators of treatment effect are unknown [0.03%]
基于标量和函数预测器构建治疗决策规则，当疗效调节剂未知时
Adam Ciarleglio,Eva Petkova,Todd Ogden et al.
Adam Ciarleglio et al.
Treatment response heterogeneity poses serious challenges for selecting treatment for many diseases. To better understand this heterogeneity and to help in determining the best patient-specific treatments for a given disease, many clinical ...
Karthik Bharath,Sebastian Kurtek,Arvind Rao et al.
Karthik Bharath et al.
We propose a curve-based Riemannian geometric approach for general shape-based statistical analyses of tumours obtained from radiologic images. A key component of the framework is a suitable metric that enables comparisons of tumour shapes,...
John B Copas,Dan Jackson,Ian R White et al.
John B Copas et al.
Univariate meta-analysis concerns a single outcome of interest measured across a number of independent studies. However, many research studies will have also measured secondary outcomes. Multivariate meta-analysis allows us to take these se...
Discussion of Laber et al. "Optimal treatment allocations in space and time for on-line control of an emerging infectious disease" [0.03%]
对Laber等人关于“时空最优治疗分配，在线控制新兴传染病”的讨论
Michael T Lawson,Hunyong Cho,Arkopal Choudhury et al.
Michael T Lawson et al.
Discussion on Optimal treatment allocations in space and time for on-line control of an emerging infectious disease [0.03%]
时空优化分配在新兴传染病在线控制中的应用讨论
Seongho Kim,Weng Kee Wong
Seongho Kim
Modelling time varying heterogeneity in recurrent infection processes: an application to serological data [0.03%]
传染病复发过程的时间变化异质性模拟：一种血清学数据应用方法
Steven Abrams,Andreas Wienke,Niel Hens
Steven Abrams
Frailty models are often used in survival analysis to model multivariate time-to-event data. In infectious disease epidemiology, frailty models have been proposed to model heterogeneity in the acquisition of infection and to accommodate ass...
Bayesian mixed treatment comparisons meta-analysis for correlated outcomes subject to reporting bias [0.03%]
考虑报告偏倚的关联结果贝叶斯混合处理比较Meta分析
Yulun Liu,Stacia M DeSantis,Yong Chen
Yulun Liu
Many randomized controlled trials (RCTs) report more than one primary outcome. As a result, multivariate meta-analytic methods for the assimilation of treatment effects in systematic reviews of RCTs have received increasing attention in the...