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作者：Lin, Zikai; Si, Yajuan; Kang, Jian
作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：Image -on -scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interven...
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作者：Lee, Hana; Qiu, Yumou; Carriquiry, Alicia; Ommen, Danica
作者单位：Iowa State University; Iowa State University; Peking University
摘要：We consider matching problems where the goal is to determine whether two observations randomly drawn from a population with multiple (sub)groups are from the same (sub)group. This is a key question in forensic science, where items with unidentified origins from suspects and crime scenes are compared to objects from a known set of sources to see if they originated from the same source. We derive the optimal matching rule under known density functions of data that minimizes the decision error pr...
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作者：Liu, Mengque; Fan, Xinyan; Ma, Shuangge
作者单位：Xi'an Jiaotong University; Renmin University of China; Renmin University of China; Yale University
摘要：Online health communities (OHCs) provide free, open, and wellresourced platforms for patients, family members, and others to discuss illnesses, express feelings, and connect with others. Linguistic analysis of OHC posts can assist in better understanding disease conditions as well as monitoring the emotional and mental status of patients and those who are closely related. Many existing OHC linguistic analyses are limited by focusing on individual words. There are a handful of cooccurrence netw...
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作者：Sun, Jiehuan; Liao, Katherine P.; Cai, Tianxi
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital; Harvard University; Harvard T.H. Chan School of Public Health
摘要：Knowledge networks, such as the healthcare delivery network (HDN), describing relationships among different medical encounters, are useful summaries of state-of-art medical knowledge. The increasing availability of longitudinal electronic health records (EHR) data promises a rich data source for learning HDN. Most existing methods for inferring knowledge networks are based on cooccurrence patterns that do not account for temporal effects or patient-level heterogeneity. In this article, buildin...
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作者：Chen, Jieyu; Janke, Tim; Steinke, Florian; Lerch, Sebastian
作者单位：Helmholtz Association; Karlsruhe Institute of Technology; Technical University of Darmstadt
摘要：Ensemble weather forecasts based on multiple runs of numerical weather prediction models typically show systematic errors and require postprocessing to obtain reliable forecasts. Accurately modeling multivariate dependencies is crucial in many practical applications, and various approaches to multivariate postprocessing have been proposed where ensemble predictions are first postprocessed separately in each margin and multivariate dependencies are then restored via copulas. These two-step meth...
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作者：Hu, Jie; Chen, Yu; Leng, Chenlei; Tang, Cheng yong
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Warwick; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：Correlated data are ubiquitous in today's data-driven society. While regression models for analyzing means and variances of responses of interest are relatively well developed, the development of these models for analyzing the correlations is largely confined to longitudinal data, a special form of sequentially correlated data. This paper proposes a new method for the analysis of correlations to fully exploit the use of covariates for general correlated data. In a renewed analysis of the class...
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作者：Gao, Yunan; Kowal, Daniel r.
作者单位：Rice University
摘要：Pollutant exposure during gestation is a known and adverse factor for birth and health outcomes. However, the links between prenatal air pollution exposures and educational outcomes are less clear, in particular, the critical windows of susceptibility during pregnancy. Using a large cohort of students in North Carolina, we study the link between prenatal daily PM2.5 exposure and fourth end-of-grade reading scores. We develop and apply a locally adaptive and highly scalable Bayesian regression ...
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作者：Bell, David R.; Ledoit, Oliver; Wolf, Michael
作者单位：University of Zurich
摘要：This paper estimates the curvature of the Earth, defined as one over its radius, without relying on physical measurements. The orthodox model states that the Earth is (nearly) spherical with a curvature of pi /20,000 km. By contrast, the heterodox flat-Earth model stipulates a curvature of zero. Abstracting from the well-worn arguments for and against both models, rebuttals and counter-rebuttals ad infinitum, we propose a novel statistical methodology based on verifiable flight times along reg...
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作者：Xu, Gang; Amei, Amei; Wu, Weimiao; Liu, Yunqing; Shen, Linchuan; Oh, Edwin C.; Wang, Zuoheng
作者单位：Nevada System of Higher Education (NSHE); University of Nevada Reno; Yale University; Nevada System of Higher Education (NSHE); University of Nevada Reno
摘要：Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fail to capture the dynamic pattern of disease progression. However, the relative i...
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作者：Dandl, Susanne; Haslinger, Christian; Hothorn, Torsten; Seibold, Heidi; Sverdrup, Erik; Wager, Stefan; Zeileis, Achim
作者单位：University of Munich; University of Zurich; University Zurich Hospital; University of Zurich; Swiss School of Public Health (SSPH+); University of Zurich; Stanford University; University of Innsbruck
摘要：Estimation of heterogeneous treatment effects (HTE) is of prime importance in many disciplines, from personalized medicine to economics among many others. Random forests have been shown to be a flexible and powerful approach to HTE estimation in both randomized trials and observational studies. In particular causal forests introduced by Athey, Tibshirani and Wager (Ann. Statist. 47 (2019) 1148-1178), along with the R implementation in package grf were rapidly adopted. A related approach, calle...
