Joseph Antonelli,Ander Wilson,Brent A Coull
Joseph Antonelli
Distributed lag models are useful in environmental epidemiology as they allow the user to investigate critical windows of exposure, defined as the time periods during which exposure to a pollutant adversely affects health outcomes. Recent s...
Nathan Dyjack,Daniel N Baker,Vladimir Braverman et al.
Nathan Dyjack et al.
A standard unsupervised analysis is to cluster observations into discrete groups using a dissimilarity measure, such as Euclidean distance. If there does not exist a ground-truth label for each observation necessary for external validity me...
Erin E Gabriel,Arvid Sjölander,Dean Follmann et al.
Erin E Gabriel et al.
When multiple mediators are present, there are additional effects that may be of interest beyond the well-known natural (NDE) and controlled direct effects (CDE). These effects cross the type of control on the mediators, setting one to a co...
Differences in set-based tests for sparse alternatives when testing sets of outcomes compared to sets of explanatory factors in genetic association studies [0.03%]
在基因关联研究中，在检验结果集合与检验原因集合时稀疏备择假设的集合检验法之间的差异性分析
Ryan Sun,Andy Shi,Xihong Lin
Ryan Sun
Set-based association tests are widely popular in genetic association settings for their ability to aggregate weak signals and reduce multiple testing burdens. In particular, a class of set-based tests including the Higher Criticism, Berk-J...
Bayesian sample size determination in basket trials borrowing information between subsets [0.03%]
借组各亚组间信息的篮子试验中的贝叶斯样本量计算方法
Haiyan Zheng,Michael J Grayling,Pavel Mozgunov et al.
Haiyan Zheng et al.
Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit bor...
Randomized Controlled Trial
Biostatistics (Oxford, England). 2023 Oct 18;24(4):1000-1016. DOI:10.1093/biostatistics/kxac033 2023
A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth [0.03%]
一种在健康分析中结合暴露不确定性的贝叶斯框架及其在空气污染与死产关系中的应用研究
Saskia Comess,Howard H Chang,Joshua L Warren
Saskia Comess
Studies of the relationships between environmental exposures and adverse health outcomes often rely on a two-stage statistical modeling approach, where exposure is modeled/predicted in the first stage and used as input to a separately fit h...
Penalized decomposition using residuals (PeDecURe) for feature extraction in the presence of nuisance variables [0.03%]
基于残差的惩罚分解特征提取算法(PeDecURe)
Sarah M Weinstein,Christos Davatzikos,Jimit Doshi et al.
Sarah M Weinstein et al.
Neuroimaging data are an increasingly important part of etiological studies of neurological and psychiatric disorders. However, mitigating the influence of nuisance variables, including confounders, remains a challenge in image analysis. In...
Tzu-Jung Huang,Alex Luedtke;AMP INVESTIGATOR GROUP
Tzu-Jung Huang
Though platform trials have been touted for their flexibility and streamlined use of trial resources, their statistical efficiency is not well understood. We fill this gap by establishing their greater efficiency for comparing the relative ...
Danni Tu,Bridget Mahony,Tyler M Moore et al.
Danni Tu et al.
Many scientific questions can be formulated as hypotheses about conditional correlations. For instance, in tests of cognitive and physical performance, the trade-off between speed and accuracy motivates study of the two variables together. ...
Yujie Wu,Benjamin Langworthy,Molin Wang
Yujie Wu
Marginal structural models (MSMs), which adopt inverse probability treatment weighting in the estimating equations, are powerful tools to estimate the causal effects of time-varying exposures in the presence of time-dependent confounders. M...