Sparse estimation for case-control studies with multiple disease subtypes [0.03%]
针对多种疾病亚型的病例对照研究的稀疏估计方法
Nadim Ballout,Cedric Garcia,Vivian Viallon
Nadim Ballout
The analysis of case-control studies with several disease subtypes is increasingly common, e.g. in cancer epidemiology. For matched designs, a natural strategy is based on a stratified conditional logistic regression model. Then, to account...
Magnus M Münch,Carel F W Peeters,Aad W Van Der Vaart et al.
Magnus M Münch et al.
In high-dimensional data settings, additional information on the features is often available. Examples of such external information in omics research are: (i) $p$-values from a previous study and (ii) omics annotation. The inclusion of this...
Diego Tomassi,Liliana Forzani,Sabrina Duarte et al.
Diego Tomassi et al.
Recent efforts to characterize the human microbiome and its relation to chronic diseases have led to a surge in statistical development for compositional data. We develop likelihood-based sufficient dimension reduction methods (SDR) to find...
Trans-ethnic meta-analysis of rare variants in sequencing association studies [0.03%]
测序关联研究中罕见变异的跨族群元分析方法研究
Jingchunzi Shi,Michael Boehnke,Seunggeun Lee
Jingchunzi Shi
Trans-ethnic meta-analysis is a powerful tool for detecting novel loci in genetic association studies. However, in the presence of heterogeneity among different populations, existing gene-/region-based rare variants meta-analysis methods ma...
Mapping epileptic directional brain networks using intracranial EEG data [0.03%]
基于颅内EEG数据绘制癫痫定向性脑网络图谱
Huazhang Li,Yaotian Wang,Seiji Tanabe et al.
Huazhang Li et al.
The human brain is a directional network system, in which brain regions are network nodes and the influence exerted by one region on another is a network edge. We refer to this directional information flow from one region to another as dire...
Measuring effects of medication adherence on time-varying health outcomes using Bayesian dynamic linear models [0.03%]
基于贝叶斯动态线性模型度量药物依从性对时间变化健康结果的影响
Luis F Campos,Mark E Glickman,Kristen B Hunter
Luis F Campos
One of the most significant barriers to medication treatment is patients' non-adherence to a prescribed medication regimen. The extent of the impact of poor adherence on resulting health measures is often unknown, and typical analyses ignor...
A local group differences test for subject-level multivariate density neuroimaging outcomes [0.03%]
一种针对多变量密度神经影像结果的受试者水平局部组间差异检验方法
Jordan D Dworkin,Kristin A Linn,Andrew J Solomon et al.
Jordan D Dworkin et al.
A great deal of neuroimaging research focuses on voxel-wise analysis or segmentation of damaged tissue, yet many diseases are characterized by diffuse or non-regional neuropathology. In simple cases, these processes can be quantified using ...
Covariate Assisted Principal regression for covariance matrix outcomes [0.03%]
辅助主成分回归的协变量用于协方差矩阵型响应变量
Yi Zhao,Bingkai Wang,Stewart H Mostofsky et al.
Yi Zhao et al.
In this study, we consider the problem of regressing covariance matrices on associated covariates. Our goal is to use covariates to explain variation in covariance matrices across units. As such, we introduce Covariate Assisted Principal (C...
A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data [0.03%]
一种贝叶斯零膨胀负二项回归模型 用于微生物组数据的整合分析
Shuang Jiang,Guanghua Xiao,Andrew Y Koh et al.
Shuang Jiang et al.
Microbiome omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with identification of specific bacteria taxa associated with diseases, recent scientific advancements provide mo...
A Gaussian copula approach for dynamic prediction of survival with a longitudinal biomarker [0.03%]
一种基于高斯copula的生存动态预测与纵向标志物相关的方法研究
Krithika Suresh,Jeremy M G Taylor,Alexander Tsodikov
Krithika Suresh
Dynamic prediction uses patient information collected during follow-up to produce individualized survival predictions at given time points beyond treatment or diagnosis. This allows clinicians to obtain updated predictions of a patient's pr...