Model-robust standardization in stepped wedge cluster randomized trials [0.03%]
分阶段楔入式群组随机试验中的模型稳健性标准化
Xi Fang,Xueqi Wang,Patrick J Heagerty et al.
Xi Fang et al.
Stepped-wedge cluster-randomized trials (SW-CRTs) are widely used in healthcare and implementation science, enabling all clusters to receive the intervention through a staggered rollout. Traditional model-based methods, including generalize...
Using case description information to reduce sensitivity to bias for the attributable fraction among the exposed [0.03%]
利用病例描述信息减少对偏差的敏感性以确定归因危险度
Kan Chen,Jing Cheng,M Elizabeth Halloran et al.
Kan Chen et al.
The attributable fraction among the exposed ( A F e ) is the proportion of disease cases among the exposed that could be avoided by eliminating the exposure. In this article, we propose a new approach to reduce sensitivity to hidden bias ...
Hiroyasu Ando,Akihiro Nishi,Mark S Handcock
Hiroyasu Ando
Repeated small dynamic networks are integral to studies in evolutionary game theory, where networked public goods games offer novel insights into human behaviours. Building on these findings, it is necessary to develop a statistical model t...
Hierarchical latent class models for mortality surveillance using partially verified verbal autopsies [0.03%]
基于部分验证的口头自述的死亡率监测的层次潜在类别模型
Yu Zhu,Zehang Richard Li
Yu Zhu
Monitoring cause-of-death data is an important part of understanding disease burdens and effects of public health interventions. Verbal autopsy (VA) is a well-established method for gathering information about deaths outside of hospitals by...
COADVISE: covariate adjustment with variable selection in randomized controlled trials [0.03%]
基于变量选择的随机对照试验协变量调整方法研究：COADVISE法及其应用分析
Yi Liu,Ke Zhu,Larry Han et al.
Yi Liu et al.
Adjusting for covariates in randomized controlled trials can enhance the credibility and efficiency of treatment effect estimation. However, handling numerous covariates and their complex (nonlinear) transformations poses a challenge. Motiv...
Incorporating external risk information with the Cox model under population heterogeneity: applications to trans-ancestry polygenic hazard scores [0.03%]
科克斯模型下的外源性风险信息的引入及在泛祖系多基因危险度评分中的应用
Di Wang,Wen Ye,Ji Zhu et al.
Di Wang et al.
Polygenic hazard scores (PHS) designed for European ancestry (EUR) individuals provide ample information regarding risk discrimination. Incorporating such information can improve the performance of risk discrimination in the target small-si...
A Bayesian mixture model approach to examining neighbourhood social determinants of health in endometrial cancer care in Massachusetts [0.03%]
马萨诸塞州子宫内膜癌护理中检查邻里社会决定因素的贝叶斯混合模型方法
Carmen B Rodríguez,Stephanie M Wu,Stephanie Alimena et al.
Carmen B Rodríguez et al.
Many studies examine social determinants of health (SDoH) in isolation, overlooking their interconnected nature. We used a multifactorial approach to construct a neighbourhood-level measure that explores how SDoH jointly impact care receive...
Improving Survey Inference in Two-phase Designs Using Bayesian Machine Learning [0.03%]
利用贝叶斯机器学习改进两阶段设计中的调查推断
Xinru Wang,Anyu Zhu,Lauren Kennedy et al.
Xinru Wang et al.
The two-phase sampling design is a cost-effective strategy widely used in public health research. Analyzing the Phase II sample often involves creating subsample-specific weights. However, these weights can be highly variable, leading to un...
Multivariate mixed models accounting for don't know options in ordinal data [0.03%]
考虑ordinal数据中的不知道选项的多元混合模型
Ralitza Gueorguieva,Maria Iannario
Ralitza Gueorguieva
Multivariate ordinal data characterised by between-subject heterogeneity or different response styles are prevalent in surveys and other observational studies. It is especially common in surveys designed to assess individual perceptions or ...