Simulating survival data with predefined censoring rates under a mixture of non-informative right censoring schemes [0.03%]
在非信息性右侧截尾方案混合情况下预定义截尾率的生存数据模拟
Fei Wan
Fei Wan
Simulation studies have been routinely used to validate the performances of statistical methods for censored survival data under various scenarios. Our previous work proposed an integrated approach of simulating right censored survival data...
Thomas G Brooks
Thomas G Brooks
Efficient schemes for sampling from the eigenvalues of the Wishart distribution have recently been described for both the standard Wishart case (where the covariance matrix is the identity) and the spiked Wishart with a single spike (where ...
BayCAR: A Bayesian based Covariate-Adaptive Randomization method for multi-arm trials [0.03%]
基于贝叶斯的协变量自适应随机化方法用于多臂试验BayCAR
Shengping Yang,Jianrong Wu
Shengping Yang
Randomization is an essential component of a successful controlled clinical trial. Many randomization methods have been developed to balance the distributions of covariates across treatment arms to remove potential confounding effects. Whil...
Likelihood-Based Inference for Semi-Parametric Transformation Cure Models with Interval Censored Data [0.03%]
区间截断数据的半参数变换治愈模型的似然推断方法研究
Suvra Pal,Sandip Barui
Suvra Pal
A simple yet effective way of modeling survival data with cure fraction is by considering Box-Cox transformation cure model (BCTM) that unifies mixture and promotion time cure models. In this article, we numerically study the statistical pr...
Bayesian variable selection for logistic regression with a differentially misclassified binary covariate [0.03%]
具有不同误分类二值协变量的逻辑回归的贝叶斯变量选择
Daniel P Beavers,Yutong Li,James D Stamey et al.
Daniel P Beavers et al.
A Bayesian approach for variable selection is developed for use in models with a misclassified binary predictor variable. We define the main outcome model containing the latent predictor, the measurement model associated with the prevalence...
Statistical methods for assessing treatment effects on ordinal outcomes using observational data [0.03%]
基于观察性研究数据的统计方法评估治疗措施对有序结局的影响
Huirong Hu,Qi Zheng,Maiying Kong
Huirong Hu
In this article, we propose a marginal structural ordinal logistic regression model (MS-OLRM) to assess treatment effects on ordinal outcomes. Many statistical methods have been developed to estimate average treatment effect (ATE) when the ...
Automated Parameter Selection in Singular Spectrum Analysis for Time Series Analysis [0.03%]
时间序列分析中奇异谱分析的自动化参数选择方法研究
James J Yang,Anne Buu
James J Yang
In spite of wide applications of the singular spectrum analysis (SSA) method, understanding how SSA reconstructs time series and eliminates noise remains challenging due to its complex process. This study provided a novel geometric perspect...
Suvra Pal
Suvra Pal
Cure rate models are mostly used to study data arising from cancer clinical trials. Its use in the context of infectious diseases has not been explored well. In 2008, Tournoud and Ecochard first proposed a mechanistic formulation of cure ra...
The Role of Weighting Adjustment for Attrition in Longitudinal Trajectory Modeling: A Simulation Study [0.03%]
纵向轨迹模型中失访加权调整作用的仿真研究
Brady T West,Yajuan Si,Yueying Hu et al.
Brady T West et al.
Most longitudinal surveys construct weights and release wave-specific weights to adjust for attrition. However, there is no clear consensus in the literature on whether or how to apply weights in longitudinal trajectory modeling. We present...
PICBayes: Bayesian proportional hazards models for partly interval-censored data [0.03%]
PICBayes：用于部分间隔审查数据的贝叶斯比例风险模型
Chun Pan,Bo Cai
Chun Pan
Partly interval-censored (PIC) data arise frequently in medical studies of diseases that require periodic examinations for symptoms of interest, such as progression-free survival and relapse-free survival. Proportional hazards (PH) model is...