Emily Somerset,Justin J Slater,Patrick E Brown
Emily Somerset
We introduce a hierarchical Bayesian framework for reconstructing epidemic curves using under-reported case counts and wastewater data. Our approach models wastewater signals as differentiable Gaussian processes, enabling inference on their...
Hiroe Seto,Shuji Kitora,Asuka Oyama et al.
Hiroe Seto et al.
In developing risk prediction models for specific diseases, it is essential to evaluate the calibration performance of the prediction model. Various methods have been proposed to assess the calibration of prediction models, but it has been ...
Semiparametric efficient estimation of small genetic effects in large-scale population cohorts [0.03%]
大规模人群队列中高效估计小规模遗传效应
Olivier Labayle,Breeshey Roskams-Hieter,Joshua Slaughter et al.
Olivier Labayle et al.
Population genetics seeks to quantify DNA variant associations with traits or diseases, as well as interactions among variants and with environmental factors. Computing millions of estimates in large cohorts in which small effect sizes and ...
A Bayesian semi-parametric approach to causal mediation for longitudinal mediators and time-to-event outcomes with application to a cardiovascular disease cohort study [0.03%]
纵向中介变量和生存终点结果的因果中介分析的一种贝叶斯半参数方法及其在心血管疾病队列研究中的应用
Saurabh Bhandari,Michael J Daniels,Maria Josefsson et al.
Saurabh Bhandari et al.
Causal mediation analysis of observational data is an important tool for investigating the potential causal effects of medications on disease-related risk factors, and on time-to-death (or disease progression) through these risk factors. Ho...
The winner's curse under dependence: repairing empirical Bayes using convoluted densities [0.03%]
相依条件下的赢家诅咒：使用卷积密度修复经验贝叶斯方法
Stijn Hawinkel,Olivier Thas,Steven Maere
Stijn Hawinkel
The winner's curse is a form of selection bias that arises when estimates are obtained for a large number of features, but only a subset of most extreme estimates is reported. It occurs in large scale significance testing as well as in rank...
Leveraging population information in brain connectivity via Bayesian ICA with a novel informative prior for correlation matrices [0.03%]
基于相关矩阵新型信息先验的贝叶斯ICA在脑连接中的人群信息挖掘方法研究
Amanda F Mejia,David Bolin,Daniel A Spencer et al.
Amanda F Mejia et al.
Brain functional connectivity (FC), the temporal synchrony between brain networks, is essential to understand the functional organization of the brain and to identify changes due to neurological disorders, development, treatment, and other ...
Model-based dimensionality reduction for single-cell RNA-seq using generalized bilinear models [0.03%]
基于广义双线性模型的单细胞RNA测序模型降维方法
Phillip B Nicol,Jeffrey W Miller
Phillip B Nicol
Dimensionality reduction is a critical step in the analysis of single-cell RNA-seq (scRNA-seq) data. The standard approach is to apply a transformation to the count matrix followed by principal components analysis (PCA). However, this appro...
Robust transfer learning for individualized treatment rules in the presence of missing data [0.03%]
缺失数据下的稳健迁移学习个体化治疗策略方法研究
Zhiyu Sui,Ying Ding,Lu Tang
Zhiyu Sui
Individualized treatment rule (ITR) is a stepping stone to precision medicine. To ensure validity, ITRs are ideally derived from randomized trial data, but the use cases of ITRs extend beyond these trial populations. Transferring knowledge ...
Control arm augmentation and hierarchical modeling in time-to-event trials: advantages and pitfalls [0.03%]
时间事件试验中的控制臂增强和分层建模：优势与陷阱
Ethan M Alt,Xiuya Chang,Qing Liu et al.
Ethan M Alt et al.
In clinical trials, it is often valuable to borrow information from external data sources. Unfortunately, when the external data are fully or partially incompatible with the current trial data, type I error rates can be highly inflated unde...
Jonathan Boss,Wei Hao,Amber Cathey et al.
Jonathan Boss et al.
Environmental health studies are increasingly measuring endogenous omics data ($ /boldsymbol{M} $) to study intermediary biological pathways by which an exogenous exposure ($ /boldsymbol{A} $) affects a health outcome ($ /boldsymbol{Y} $), ...