Stéphane Guerrier,Roberto Molinari,Maria-Pia Victoria-Feser et al.
Stéphane Guerrier et al.
Latent time series models such as (the independent sum of) ARMA(p, q) models with additional stochastic processes are increasingly used for data analysis in biology, ecology, engineering, and economics. Inference on and/or prediction from t...
Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle [0.03%]
基于肌动蛋白的单细胞三维基因组和表观遗传数据张量联合建模
Kwangmoon Park,Sündüz Keleş
Kwangmoon Park
Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with th...
Generalizing the intention-to-treat effect of an active control from historical placebo-controlled trials: A case study of the efficacy of daily oral TDF/FTC in the HPTN 084 study [0.03%]
从历史安慰剂对照试验推广积极对照的意向性治疗效应：HPTN 084 研究中每日口服替诺福韦地索普西富马酸福米特拉匹韦有效性的案例研究
Qijia He,Fei Gao,Oliver Dukes et al.
Qijia He et al.
In many clinical settings, an active-controlled trial design (e.g., a non-inferiority or superiority design) is often used to compare an experimental medicine to an active control (e.g., an FDA-approved, standard therapy). One prominent exa...
Dissecting gene expression heterogeneity: generalized Pearson correlation squares and the K-lines clustering algorithm [0.03%]
解析基因表达异质性：广义皮尔逊相关平方和K线聚类算法
Jingyi Jessica Li,Heather J Zhou,Peter J Bickel et al.
Jingyi Jessica Li et al.
Motivated by the pressing needs for dissecting heterogeneous relationships in gene expression data, here we generalize the squared Pearson correlation to capture a mixture of linear dependences between two real-valued variables, with or wit...
Zhanrui Cai,Jing Lei,Kathryn Roeder
Zhanrui Cai
Test of independence is of fundamental importance in modern data analysis, with broad applications in variable selection, graphical models, and causal inference. When the data is high dimensional and the potential dependence signal is spars...
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies [0.03%]
极大极小效应的统计推断：跨多个研究识别稳定的关联
Zijian Guo
Zijian Guo
Integrative analysis of data from multiple sources is critical to making generalizable discoveries. Associations consistently observed across multiple source populations are more likely to be generalized to target populations with possible ...
Leo L Duan,Arkaprava Roy;Alzheimer’s Disease Neuroimaging Initiative
Leo L Duan
Spectral clustering views the similarity matrix as a weighted graph, and partitions the data by minimizing a graph-cut loss. Since it minimizes the across-cluster similarity, there is no need to model the distribution within each cluster. A...
Guilherme Duarte,Noam Finkelstein,Dean Knox et al.
Guilherme Duarte et al.
Applied research conditions often make it impossible to point-identify causal estimands without untenable assumptions. Partial identification-bounds on the range of possible solutions-is a principled alternative, but the difficulty of deriv...
Rank-Based Greedy Model Averaging for High-Dimensional Survival Data [0.03%]
基于等级的贪婪模型平均方法及其在高维生存数据分析中的应用
Baihua He,Shuangge Ma,Xinyu Zhang et al.
Baihua He et al.
Model averaging is an effective way to enhance prediction accuracy. However, most previous works focus on low-dimensional settings with completely observed responses. To attain an accurate prediction for the risk effect of survival data wit...
Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness [0.03%]
测试阴性设计的疫苗效果研究中的双重阴性对照推断
Kendrick Qijun Li,Xu Shi,Wang Miao et al.
Kendrick Qijun Li et al.
The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world settings, such as Influenza, Rotavirus, Dengue fever, and more recently COVID-19...