Yachong Yang,Arun Kumar Kuchibhotla,Eric Tchetgen Tchetgen
Yachong Yang
Conformal prediction has received tremendous attention in recent years and has offered new solutions to problems in missing data and causal inference; yet these advances have not leveraged modern semi-parametric efficiency theory for more e...
T Tony Cai,Zheng T Ke,Paxton Turner
T Tony Cai
Motivated by applications in text mining and discrete distribution inference, we test for equality of probability mass functions of K groups of high-dimensional multinomial distributions. Special cases of this problem include global testing...
GENIUS-MAWII: for robust Mendelian randomization with many weak invalid instruments [0.03%]
具有许多弱无效工具的稳健孟德尔随机化方法（GENIUS-MAWII）
Ting Ye,Zhonghua Liu,Baoluo Sun et al.
Ting Ye et al.
Mendelian randomization (MR) addresses causal questions using genetic variants as instrumental variables. We propose a new MR method, G-Estimation under No Interaction with Unmeasured Selection (GENIUS)-MAny Weak Invalid IV, which simultane...
Gradient synchronization for multivariate functional data, with application to brain connectivity [0.03%]
多变量功能数据的梯度同步及其在脑连接性中的应用
Yaqing Chen,Shu-Chin Lin,Yang Zhou et al.
Yaqing Chen et al.
Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important application is the problem of assess...
Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis [0.03%]
复合零假设的自适应自助法在中介效应路径分析中的应用
Yinqiu He,Peter X K Song,Gongjun Xu
Yinqiu He
Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of attention due to the tremendous need for such analyses in scient...
Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding [0.03%]
使用双重阴性对照识别和估计因果同辈效应以解决未测量到的网络混淆问题
Naoki Egami,Eric J Tchetgen Tchetgen
Naoki Egami
Identification and estimation of causal peer effects are challenging in observational studies for two reasons. The first is the identification challenge due to unmeasured network confounding, for example, homophily bias and contextual confo...
Daiwei Zhang,Lexin Li,Chandra Sripada et al.
Daiwei Zhang et al.
Delineating associations between images and covariates is a central aim of imaging studies. To tackle this problem, we propose a novel non-parametric approach in the framework of spatially varying coefficient models, where the spatially var...
Monotone response surface of multi-factor condition: estimation and Bayes classifiers [0.03%]
多因子条件下单态响应面：估计和Bayes分类器
Ying Kuen Cheung,Keith M Diaz
Ying Kuen Cheung
We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called PIPE-classifiers) is a projection of Bayes classifiers on the const...
Spatial confidence regions for combinations of excursion sets in image analysis [0.03%]
图像分析中游程集组合的空间置信区域
Thomas Maullin-Sapey,Armin Schwartzman,Thomas E Nichols
Thomas Maullin-Sapey
The analysis of excursion sets in imaging data is essential to a wide range of scientific disciplines such as neuroimaging, climatology, and cosmology. Despite growing literature, there is little published concerning the comparison of proce...
Hongxiang Qiu,Edgar Dobriban,Eric Tchetgen Tchetgen
Hongxiang Qiu
Predicting sets of outcomes-instead of unique outcomes-is a promising solution to uncertainty quantification in statistical learning. Despite a rich literature on constructing prediction sets with statistical guarantees, adapting to unknown...