A two-stage approach for segmenting spatial point patterns applied to multiplex imaging [0.03%]
应用于多重图像的分段空间点模式的两阶段方法
Alvin Sheng,Brian J Reich,Ana-Maria Staicu et al.
Alvin Sheng et al.
Recent advances in multiplex imaging have enabled researchers to locate different types of cells within a tissue sample. This is especially relevant for tumor immunology, as clinical regimes corresponding to different stages of disease or r...
Xi Fang,Hajime Uno,Fan Li
Xi Fang
Composite endpoints are frequently used in clinical trials to enhance the event rate and improve the statistical power. In the presence of a terminal event, the while-alive cumulative frequency measure offers a useful alternative to define ...
High-dimensional inference for functional regression with an application to the Alzheimer's disease magnetoencephalography study [0.03%]
高维函数回归的统计推断及其在阿尔兹海默症脑电研究中的应用
Huaqing Jin,Fei Jiang
Huaqing Jin
Alzheimer's disease (AD) is a progressive, chronic neurodegenerative disorder affecting millions worldwide. A new clinical magnetoencephalography (MEG) study was conducted to identify neural activity biomarkers and key brain regions in AD. ...
Bayesian scalar-on-tensor regression using the Tucker decomposition for sparse spatial modeling [0.03%]
基于 Tucker 分解的贝叶斯标量张量回归及其在稀疏空间建模中的应用
Daniel A Spencer,Rene Gutierrez,Rajarshi Guhaniyogi et al.
Daniel A Spencer et al.
Modeling with multidimensional arrays, or tensors, often presents a problem due to high dimensionality. In addition, these structures typically exhibit inherent sparsity, requiring the use of regularization methods to properly characterize ...
Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learning [0.03%]
基于统计机器学习的多研究R-learner：估计跨学科的异质性治疗效应
Cathy Shyr,Boyu Ren,Prasad Patil et al.
Cathy Shyr et al.
Heterogeneous treatment effect (HTE) refers to the nonrandom, explainable variation in treatment effects for individuals in a population. HTE estimation is central to precision medicine, where accurate effect estimates can inform personaliz...
Assessing spatial disparities: a Bayesian linear regression approach [0.03%]
基于Bayesian线性回归的评价模型应用于PM2.5空间差异估算研究
Kyle Wu,Sudipto Banerjee
Kyle Wu
Epidemiological investigations of regionally aggregated spatial data often involve detecting spatial health disparities among neighboring regions on a map of disease mortality or incidence rates. Analyzing such data introduces spatial depen...
Network generalized estimating equations for complexly correlated data with applications to cluster randomized trials [0.03%]
复杂相关数据的网络广义估计方程及其在群随机化试验中的应用
Tom Chen,Fan Li,Rui Wang
Tom Chen
Estimating parameters corresponding to mean outcomes and their intricate association structures in cluster randomized trials (CRTs) can pose significant methodological challenges. This paper introduces a novel framework that leverages netwo...
Solvejg Wastvedt,Jared D Huling,Julian Wolfson
Solvejg Wastvedt
While methods for measuring and correcting differential performance in risk prediction models have proliferated in recent years, most existing techniques can only be used to assess fairness across relatively large subgroups. The purpose of ...
Instrumental variable approach to estimating individual causal effects in N-of-1 trials: application to ISTOP study [0.03%]
N-of-1试验中估计个体因果效应的工具变量法及其在ISTOP研究中的应用
Kexin Qu,Christopher H Schmid,Tao Liu
Kexin Qu
An N-of-1 trial is a multiple crossover trial conducted in a single individual to provide evidence to directly inform personalized treatment decisions. Advances in wearable devices greatly improved the feasibility of adopting these trials t...
Decomposition of longitudinal disparities: an application to the fetal growth-singletons study [0.03%]
纵向差异的分解——一项关于单胎胎儿生长的研究应用
Sang Kyu Lee,Seonjin Kim,Mi-Ok Kim et al.
Sang Kyu Lee et al.
Addressing health disparities across demographic groups remains a critical challenge in public health, with significant gaps in understanding how these disparities evolve over time. This paper extends the traditional Peters-Belson decomposi...