A flexible bivariate cure model with shared random effect and associated inference and application to diabetic retinopathy data [0.03%]
一个灵活的双变量治愈模型及其在糖尿病视网膜病变数据上的应用与推理相关性研究
Saptangshu Nandi,Sandip Barui,Debanjan Mitra et al.
Saptangshu Nandi et al.
In lifetime studies, a proportion of subjects may never experience the event of interest, giving rise to the notion of cure rate. While traditional cure models address this in univariate set-up, many applications involve paired lifetimes, s...
Mahsa Ashouri,Nicholas C Henderson
Mahsa Ashouri
Developing tools for estimating heterogeneous treatment effects (HTEs) and individualized treatment effects has been an area of active research in recent years. While these tools have proven to be useful in many contexts, a concern when dep...
A flexible rank-based framework for individualized treatment selection with mixed-type multivariate outcomes [0.03%]
一种灵活的基于秩的个体化治疗选择框架：用于混合类型多变量结果
Chathura Siriwardhana,Bakeerathan Gunaratnam,Karunarathna Bandara Kulasekera
Chathura Siriwardhana
Personalized treatment selection is often based on a single primary endpoint, even though complex diseases are typically monitored using multiple, heterogeneous outcomes. We develop a rank-based framework for individualized treatment select...
Adaptive spline-based weighting functions for blended survival curve extrapolation [0.03%]
自适应样条函数在生存分析曲线外推中的应用
Hao Chen,Clara Grazian
Hao Chen
Health technology assessment frequently requires survival predictions well beyond the observed trial follow-up, yet single parametric models fitted to short horizons can accumulate long-term bias. Current guidance also encourages the princi...
A comparison of missing data approaches for linear regression with missing not at random outcome and predictors [0.03%]
缺失结果和预测变量的线性回归中缺失数据方法的比较
Tetiana Gorbach,Tim P Morris,James R Carpenter
Tetiana Gorbach
While most methods for missing not at random (MNAR) data in regression models address MNAR outcomes assuming fully observed predictors, real-world observational health and longitudinal studies often violate this assumption. This paper compa...
Jinhong Cui,Xiaoxiao Zhou,Melissa J Smith et al.
Jinhong Cui et al.
Mediation analysis is a powerful tool for exploring the causal relationships between exposures and outcomes that are mediated by intermediate variables. In this paper, we propose a flexible Bayesian mediation analysis framework to accommoda...
Estimating transmission parameters from stochastic epidemic models using survival analysis techniques [0.03%]
利用生存分析技术从随机流行病模型中估计传播参数
Hein Putter,Chengyuan Lu,Jacco Wallinga
Hein Putter
Compartmental models based on ordinary differential equations quantifying the interactions between susceptible, infectious and recovered individuals within a population have played an important role in infectious disease modelling. The aim ...
A more interpretable regression model for count data with excess of zeros [0.03%]
一种解释性更强的零膨胀计数数据回归模型
Gustavo H A Pereira,Jeremias Leao,Manoel Santos-Neto et al.
Gustavo H A Pereira et al.
Count data are common in medical research. When these data have more zeros than expected by the most used count distributions, it is common to employ a zero-inflated regression model. However, the interpretability of these models is much lo...
Nonparametric inference for the localization receiver operating characteristic curve and its extension to free-response image localization tasks [0.03%]
非参数化定位接收操作特性曲线的推理及其在自由响应图像定位任务中的扩展应用
Kaiyuan Liu,Xiao-Hua Zhou
Kaiyuan Liu
The localization receiver operating characteristic (LROC) and the free-response receiver operating characteristic (FROC) curves are popular methods for evaluating the performance of diagnostic tests concerning detecting and locating lesions...
Nonparametric change-point control charts for joint monitoring of mean and covariance with application to medical imaging data [0.03%]
一类非参数变化点控制图及其在医学图像数据中的应用
Guojun Liu,Jyun-You Chiang,Wen Liu et al.
Guojun Liu et al.
Monitoring medical imaging data is increasingly important in healthcare because image-derived quantitative features provide valuable information for assessing disease progression, diagnostic quality, and process stability. However, such dat...