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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：Su, Erica; Weiss, Robert E.; Nouri-Mahdavi, Kouros; Holbrook, Andrew J.
作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA
摘要：We model longitudinal macular thickness measurements to monitor the course of glaucoma and prevent vision loss due to disease progression. The macular thickness varies over a 6 x 6 grid of locations on the retina, with additional variability arising from the imaging process at each visit. Currently, ophthalmologists estimate slopes using repeated simple linear regression for each subject and location. To estimate slopes more precisely, we develop a novel Bayesian hierarchical model for multipl...
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作者：Li, Shaobo; Fan, Zhaohu; Liu, Ivy; Morrison, Philip S.; Liu, Dungang
作者单位：University of Kansas; University System of Georgia; Georgia Institute of Technology; Victoria University Wellington; Victoria University Wellington; University System of Ohio; University of Cincinnati
摘要：This paper is motivated by the analysis of a survey study focusing on college student well-being before and after the COVID-19 pandemic outbreak. A statistical challenge in well-being studies lies in the multidimensionality of outcome variables, recorded in various scales such as continuous, binary, or ordinal. The presence of mixed data complicates the examination of their relationships when adjusting for important covariates. To address this challenge, we propose a unifying framework for stu...
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作者：Li, Yujia; Liu, Peng; Wang, Wenjia; Ong, Wei; Fang, Yusi; Rren, Zhao; Tang, Lu; Celedon, Juan c.; Oesterreich, Steffi; Tseng, George c.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：With advances in high-throughput technology, molecular disease subtyping by high-dimensional omics data has been recognized as an effective approach for identifying subtypes of complex diseases with distinct disease mechanisms and prognoses. Conventional cluster analysis takes omics data as input and generates patient clusters with similar gene expression pattern. The omics data, however, usually contain multifaceted cluster structures that can be defined by different sets of genes. If the gen...
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作者：Economou, Theodoros; Johnson, Catrina; Dyson, Elizabeth
作者单位：Met Office - UK
摘要：Weather observations are important for a wide range of applications although they do pose statistical challenges, such as missing values, errors, flawed outliers and poor spatial and temporal coverage to name a few. A Bayesian hierarchical spline framework is presented here to deal with such challenges in temperature time series. Motivated by a real-life problem, the approach uses penalised splines, constructed hierarchically, to pool the data, along with a discrete mixture distribution to dea...
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作者：Xu, Tianchen; Chen, Kun; Li, Gen
作者单位：Bristol-Myers Squibb; University of Connecticut; University of Michigan System; University of Michigan
摘要：Multivariate longitudinal data are frequently encountered in practice such as in our motivating longitudinal microbiome study. It is of general interest to associate such high -dimensional, longitudinal measures with some univariate continuous outcome. However, incomplete observations are common in a regular study design, as not all samples are measured at every time point, giving rise to the so-called blockwise missing values. Such missing structure imposes significant challenges for associat...
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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...
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作者：Koh, Jonathan; Pimont, Francois; Dupuy, Jean-Luc; Opitz, Thomas
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Bern; INRAE; INRAE
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作者：Mclaughlin, Katherine R.; Johnston, Lisa G.; Jakupi, Xhevat; Gexha-bunjaku, Dafina; Deva, Edona; Handcock, Mark S.
作者单位：Oregon State University; University of California System; University of California Los Angeles
摘要：Respondent -driven sampling (RDS) is used throughout the world to estimate prevalence and population size for hidden populations. Although RDS is an effective method for enrolling people from key populations in studies, it relies on a partially unknown sampling mechanism, and thus each individual's inclusion probability is unknown. Current estimators for population prevalence, population size, and other outcomes rely on a participant's network size (degree) to approximate their inclusion proba...
