Consensus spectral clustering with weighted similarity functions for single-cell RNA sequencing data [0.03%]
基于加权相似性函数的单细胞RNA序列分批共识谱聚类
Xiaodan Zhu,Zhide Fang
Xiaodan Zhu
In this paper, we explore unsupervised clustering algorithms on real-world single-cell RNA-sequencing datasets. While single-cell RNA sequencing technologies have revolutionized the ability to profile gene expression at the resolution of in...
Commensurate prior models with random effects for interval-censored data to accommodate historical controls [0.03%]
允许历史对照的区间删失数据下的共先验模型及其随机效应模型
Xi Fang,Brent Logan,Anjishnu Banerjee et al.
Xi Fang et al.
Using historical controls for clinical trial data analysis may increase statistical power and reduce required sample sizes when studying rare diseases. Most existing literature on borrowing information from historical controls with survival...
A New Estimation Algorithm for Destructive Cure Model: Illustration with Exponentially Weighted Poisson Competing Risks [0.03%]
一个新的破坏性愈合模型估计算法：指数加权泊松竞争风险的说明
Suvra Pal,Souvik Roy
Suvra Pal
We propose an improved estimation method for the destructive cure rate model by introducing a generic maximum likelihood algorithm, the sequential quadratic Hamiltonian (SQH) scheme, which employs a gradient-free optimization approach. The ...
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...