Baosheng Liang,Xingwei Tong,Donglin Zeng et al.
Baosheng Liang et al.
In many clinical studies, patients may be asked to report their medication adherence, presence of side effects, substance use, and hospitalization information during the study period. However, the exact occurrence time of these recurrent ev...
A MULTIVARIATE GAUSSIAN PROCESS FACTOR MODEL FOR HAND SHAPE DURING REACH-TO-GRASP MOVEMENTS [0.03%]
用于到达并抓握过程中手形变化的多元高斯过程因子模型
Lucia Castellanos,Vincent Q Vu,Sagi Perel et al.
Lucia Castellanos et al.
We propose a Multivariate Gaussian Process Factor Model to estimate low dimensional spatio-temporal patterns of finger motion in repeated reach-to-grasp movements. Our model decomposes and reduces the dimensionality of variation of the mult...
Runze Li,Jingyuan Liu,Lejia Lou
Runze Li
Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper a...
CONTROL FUNCTION ASSISTED IPW ESTIMATION WITH A SECONDARY OUTCOME IN CASE-CONTROL STUDIES [0.03%]
病例对照研究中借助辅助信息的逆概率加权法估计次要结局效应
Tamar Sofer,Marilyn C Cornelis,Peter Kraft et al.
Tamar Sofer et al.
Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcome...
Tamar Sofer,Lee Dicker,Xihong Lin
Tamar Sofer
We consider variable selection for high-dimensional multivariate regression using penalized likelihoods when the number of outcomes and the number of covariates might be large. To account for within-subject correlation, we consider variable...
T Tony Cai,Hongzhe Li,Weidong Liu et al.
T Tony Cai et al.
Motivated by analysis of gene expression data measured in different tissues or disease states, we consider joint estimation of multiple precision matrices to effectively utilize the partially shared graphical structures of the corresponding...
Dan Shen,Haipeng Shen,Hongtu Zhu et al.
Dan Shen et al.
The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirecti...
Xinyu Zhang,Guohua Zou,Raymond J Carroll
Xinyu Zhang
This paper proposes a model averaging method based on Kullback-Leibler distance under a homoscedastic normal error term. The resulting model average estimator is proved to be asymptotically optimal. When combining least squares estimators, ...
TIME-VARYING COEFFICIENT MODELS FOR JOINT MODELING BINARY AND CONTINUOUS OUTCOMES IN LONGITUDINAL DATA [0.03%]
纵向数据分析中基于时变系数方法的联合建模研究
Esra Kürüm,Runze Li,Saul Shiffman et al.
Esra Kürüm et al.
Motivated by an empirical analysis of ecological momentary assessment data (EMA) collected in a smoking cessation study, we propose a joint modeling technique for estimating the time-varying association between two intensively measured long...
Partial linear varying multi-index coefficient model for integrative gene-environment interactions [0.03%]
部分线性变系数多指标基因与环境联合效应模型
Xu Liu,Yuehua Cui,Runze Li
Xu Liu
Gene-environment (G×E) interactions play key roles in many complex diseases. An increasing number of epidemiological studies have shown the combined effect of multiple environmental exposures on disease risk. However, no appropriate statis...