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作者：Dai, Wei; Zhang, Heping
作者单位：Yale University
摘要：Understanding the genetic architecture of brain functions is essential to clarify the biological etiologies of behavioral and psychiatric disorders. Functional connectivity, representing pairwise correlations of neural activities between brain regions, is moderately heritable. Current methods to identify single nucleotide polymorphisms (SNPs) linked to functional connectivity either neglect the complex structure of functional connectivity or fail to control false discoveries. Therefore, we pro...
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作者：Hyun, Sangwon
作者单位：University of California System; University of California Santa Cruz
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作者：Sit, Tony
作者单位：Chinese University of Hong Kong
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作者：Pesta, Michal
作者单位：Charles University Prague
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作者：Fu, Chenqi; Zhou, Shouhao; Lee, J. Jack
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; University of Texas System; UTMD Anderson Cancer Center
摘要：Interval-based designs represent cutting-edge adaptive methodologies for phase I clinical trials to identify the maximum tolerated dose (MTD). These designs exhibit robust performance comparable to more intricate, model-based designs, and their pretabulated decision rule enables them to be implemented as simply as the conventional algorithm-based designs. In this paper, we introduce the posterior predictive (PoP) design, a novel interval-based design that leverages advanced Bayesian predictive...
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作者：Liu, Siyan; Yeh, Chi-Kuang; Zhang, Xin; Tian, Qinglong; Li, Pengfei
作者单位：East China Normal University; University of Waterloo
摘要：This study introduces a new approach to addressing the positive and unlabeled (PU) data through the double exponential tilting model (DETM) under a transfer learning framework. Traditional methods often fall short because they only apply to the common distributions (CD) PU data (also known as the selected completely at random PU data), where the labeled positive and unlabeled positive data are assumed to be from the same distribution. In contrast, our DETM's dual structure effectively accommod...
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作者：Chen, Yang
作者单位：University of Michigan System; University of Michigan
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作者：Leiner, James; Duan, Boyan; Wasserman, Larry; Ramdas, Aaditya
作者单位：Carnegie Mellon University; Carnegie Mellon University; Alphabet Inc.; Google Incorporated
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作者：McCartan, Cory; Fisher, Robin; Goldin, Jacob; Ho, Daniel E.; Imai, Kosuke
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; United States Department of the Treasury; University of Chicago; National Bureau of Economic Research; Stanford University; Stanford University; Harvard University; Harvard University
摘要：Estimating racial disparities without access to individual-level racial information is a common challenge in economic and policy settings. We develop a statistical method that relaxes the strong independence assumption of common race imputation approaches like Bayesian-Improved Surname Geocoding (BISG). Our identification assumption is that surname is conditionally independent of the outcome given (unobserved) race, residence location, and other observed characteristics. The proposed approach ...
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作者：Kirichenko, Alisa; Kelly, Luke J.; Koskela, Jere
作者单位：University of Warwick; University College Cork; Newcastle University - UK
摘要：We derive tractable criteria for the consistency of Bayesian tree reconstruction procedures, which constitute a central class of algorithms for inferring common ancestry among DNA sequence samples in phylogenetics. Our results encompass several Bayesian algorithms in widespread use, such as BEAST, MrBayes, and RevBayes. Unlike essentially all existing asymptotic guarantees for tree reconstruction, we require no discretization or boundedness assumptions on branch lengths. Our results are also v...
