Lola Etiévant
Lola Etiévant
Studies of HPV vaccine efficacy usually record infections with vaccine targeted and non-targeted strains. Contrary to blinded randomized controlled trials, confounding bias can be a threat and risk compensation may occur in observational st...
Targeted maximum likelihood estimation (TMLE) in regulatory submissions and research: a landscape analysis [0.03%]
基于最大靶向似然估计（TMLE）的监管提交和研究现状分析
Hana Lee,Menglun Wang,Spencer Haupert et al.
Hana Lee et al.
Targeted Maximum Likelihood Estimation, also referred to as Targeted Minimum Loss Estimation (TMLE), is a statistical method that enables causal inference while incorporating flexible, advanced machine learning techniques. Within the drug d...
Predicting birth weight by multivariate functional principal component regressions [0.03%]
基于多元函数主成分回归的出生体重预测模型
Yaeji Lim,Ruijin Lu,Madeleine St Ville et al.
Yaeji Lim et al.
Functional data analysis (FDA) provides a powerful statistical framework for analyzing complex data, such as curves or functions, over high-dimensional domains. In this paper, we focus on functional predictor regression (scalar-on-function)...
Robust median regression for count data with general lower truncation using a contaminated discrete Weibull model [0.03%]
使用受污染的离散Weibull模型进行一般下截断计数数据的鲁棒中位数回归
Divan A Burger,Janet van Niekerk,Emmanuel Lesaffre
Divan A Burger
In right-skewed count data, the mean is disproportionately affected by a long upper tail, whereas the median remains a more representative measure of central tendency. Discrete Weibull (DW) regression links covariates to a shifted median, w...
Handling the uncertainty issue of missingness via a mixture-structure-based method [0.03%]
基于混合结构的方法处理缺失性不确定性问题
Wenxiao Zhou,Bo Fu
Wenxiao Zhou
Missing data are common in real-world studies, yet the underlying missingness structure is often unknown, bringing additional uncertainty before an appropriate inference method can be applied. In this paper, we systematically examine two so...
Statistical method for pooling categorical biomarker data from multi-center matched/nested case-control studies [0.03%]
多中心匹配或嵌套病例对照研究中分类生物标志物数据汇总分析的统计方法研究
Yujie Wu,Xiao Wu,Ce Yang et al.
Yujie Wu et al.
Pooled analyses that aggregate data from multiple studies are becoming increasingly common in collaborative epidemiologic research to increase sample size and population diversity. Many biomarkers, such as vitamin D, are routinely analyzed ...
Chamika Porage,Ingeborg Waernbaum
Chamika Porage
The prognostic score (PGS) is a function of observed covariates that summarizes covariates' association with potential responses. In the current study, we propose a full prognostic score (FPGS), an extension of the PGS that integrates indiv...
Performance evaluation of dimensionality reduction techniques on high-dimensional DNA methylation data [0.03%]
高维DNA甲基化数据的降维方法性能评估
Kuldeep Kumar Sharma,Kuppan Gokulakrishnan,Binu V S et al.
Kuldeep Kumar Sharma et al.
DNA methylation (DNAm) is a key epigenetic modification, and datasets capturing DNAm are typically high-dimensional. Although dimension reduction (DR) techniques are commonly applied, it remains unclear how different DR methods perform spec...
A nonparametric dependent competing risk method for net survival analysis [0.03%]
一种非参数竞争风险法在净生存分析中的应用
Reuben Adatorwovor,Aurelien Latouche,Jason P Fine
Reuben Adatorwovor
Quantifying disease-specific survival in patients with competing risks is generally done when reliable cause of death (CoD) information is available. With known CoD, cause-specific and cumulative incidence functions for competing risk data ...
Benchmarking multi-step methods for the dynamic prediction of survival with numerous longitudinal predictors [0.03%]
具有众多纵向预测指标的生存动态预测的多步方法基准测试
Signorelli Mirko,Sophie Retif
Signorelli Mirko
In recent years, the growing availability of biomedical datasets featuring numerous longitudinal covariates has motivated the development of several multi-step methods for the dynamic prediction of survival outcomes. These methods employ ei...