Estimation for the bivariate quantile varying coefficient model with application to diffusion tensor imaging data analysis [0.03%]
双变量分位数变系数模型的估计及其在扩散张量成像数据分析中的应用
Matthew Pietrosanu,Haoxu Shu,Bei Jiang et al.
Matthew Pietrosanu et al.
Despite interest in the joint modeling of multiple functional responses such as diffusion properties in neuroimaging, robust statistical methods appropriate for this task are lacking. To address this need, we propose a varying coefficient q...
Rui Chen,Guanhua Chen,Menggang Yu
Rui Chen
Scientists frequently generalize population level causal quantities such as average treatment effect from a source population to a target population. When the causal effects are heterogeneous, differences in subject characteristics between ...
Tailored Bayes: a risk modeling framework under unequal misclassification costs [0.03%]
定制贝叶斯算法：不同错误代价下的风险建模框架
Solon Karapanagiotis,Umberto Benedetto,Sach Mukherjee et al.
Solon Karapanagiotis et al.
Risk prediction models are a crucial tool in healthcare. Risk prediction models with a binary outcome (i.e., binary classification models) are often constructed using methodology which assumes the costs of different classification errors ar...
A sparse negative binomial mixture model for clustering RNA-seq count data [0.03%]
一种稀疏负二项式混合模型 用于RNA测序计数数据的聚类
Yujia Li,Tanbin Rahman,Tianzhou Ma et al.
Yujia Li et al.
Clustering with variable selection is a challenging yet critical task for modern small-n-large-p data. Existing methods based on sparse Gaussian mixture models or sparse $K$-means provide solutions to continuous data. With the prevalence of...
Bayesian adaptive model selection design for optimal biological dose finding in phase I/II clinical trials [0.03%]
贝叶斯自适应模型选择设计在一期/二期临床试验中寻找最佳生物剂量的优化方法
Ruitao Lin,Guosheng Yin,Haolun Shi
Ruitao Lin
Identification of the optimal dose presents a major challenge in drug development with molecularly targeted agents, immunotherapy, as well as chimeric antigen receptor T-cell treatments. By casting dose finding as a Bayesian model selection...
Nathan W Bean,Joseph G Ibrahim,Matthew A Psioda
Nathan W Bean
Multiregional clinical trials (MRCTs) provide the benefit of more rapidly introducing drugs to the global market; however, small regional sample sizes can lead to poor estimation quality of region-specific effects when using current statist...
A Bayesian nonparametric model for classification of longitudinal profiles [0.03%]
纵向心理轮廓分类的贝叶斯非参数模型
Jeremy T Gaskins,Claudio Fuentes,Rolando De La Cruz
Jeremy T Gaskins
Across several medical fields, developing an approach for disease classification is an important challenge. The usual procedure is to fit a model for the longitudinal response in the healthy population, a different model for the longitudina...
Statistical modeling of longitudinal medical cost trajectory: renal cell cancer care cost analyses [0.03%]
纵向医学成本轨迹的统计建模：肾细胞癌护理成本分析
Shikun Wang,Yu Shen,Ya-Chen Tina Shih et al.
Shikun Wang et al.
Estimating the current cost of cancer care is important to health policy makers. An indispensable step in cost projection is to estimate cost trajectories from an incident cohort of cancer patients using longitudinal medical cost data, acco...
Corrigendum to: Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank [0.03%]
Cox模型中Lasso方法的快速算法及其在UK Biobank中的应用補遺
Ruilin Li,Christopher Chang,Johanne M Justesen et al.
Ruilin Li et al.
Published Erratum
Biostatistics (Oxford, England). 2022 Apr 13;23(2):683. DOI:10.1093/biostatistics/kxab019 2022
Smaller p-values in genomics studies using distilled auxiliary information [0.03%]
利用精炼的辅助信息缩小基因组研究中的p值大小
Jordan G Bryan,Peter D Hoff
Jordan G Bryan
Medical research institutions have generated massive amounts of biological data by genetically profiling hundreds of cancer cell lines. In parallel, academic biology labs have conducted genetic screens on small numbers of cancer cell lines ...