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作者：Luo, Xiaokang; Dasgupta, Tirthankar; Xie, Minge; Liu, Regina Y.
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：The flexibility and wide applicability of the Fisher randomization test (FRT) make it an attractive tool for assessment of causal effects of interventions from modern-day randomized experiments that are increasing in size and complexity. This paper provides a theoretical inferential framework for FRT by establishing its connection with confidence distributions. Such a connection leads to development's of (i) an unambiguous procedure for inversion of FRTs to generate confidence intervals with g...
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作者：Ignatiadis, Nikolaos; Huber, Wolfgang
作者单位：Stanford University; European Molecular Biology Laboratory (EMBL)
摘要：A fundamental task in the analysis of data sets with many variables is screening for associations. This can be cast as a multiple testing task, where the objective is achieving high detection power while controlling type I error. We consider m hypothesis tests represented by pairs ((Pi,Xi))1 <= i <= m of p-values Pi and covariates Xi, such that Pi perpendicular to Xi if Hi is null. Here, we show how to use information potentially available in the covariates about heterogeneities among hypothes...
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作者：Chen, Xu; Tokdar, Surya T.
作者单位：Duke University
摘要：Linear quantile regression is a powerful tool to investigate how predictors may affect a response heterogeneously across different quantile levels. Unfortunately, existing approaches find it extremely difficult to adjust for any dependency between observation units, largely because such methods are not based upon a fully generative model of the data. For analysing spatially indexed data, we address this difficulty by generalizing the joint quantile regression model of Yang and Tokdar (Journal ...
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作者：Wang, Xiangyu; Leng, Chenlei; Boot, Tom
作者单位：Alphabet Inc.; Google Incorporated; University of Warwick; University of Groningen
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作者：Windmeijer, Frank; Liang, Xiaoran; Hartwig, Fernando P.; Bowden, Jack
作者单位：University of Oxford; University of Oxford; University of Bristol; University of Bristol; University of Exeter
摘要：We propose a new method, the confidence interval (CI) method, to select valid instruments from a larger set of potential instruments for instrumental variable (IV) estimation of the causal effect of an exposure on an outcome. Invalid instruments are such that they fail the exclusion conditions and enter the model as explanatory variables. The CI method is based on the CIs of the per instrument causal effects estimates and selects the largest group with all CIs overlapping with each other as th...
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作者：Rossell, David; Abril, Oriol; Bhattacharya, Anirban
作者单位：Pompeu Fabra University; Texas A&M University System; Texas A&M University College Station
摘要：We propose the approximate Laplace approximation (ALA) to evaluate integrated likelihoods, a bottleneck in Bayesian model selection. The Laplace approximation (LA) is a popular tool that speeds up such computation and equips strong model selection properties. However, when the sample size is large or one considers many models the cost of the required optimizations becomes impractical. ALA reduces the cost to that of solving a least-squares problem for each model. Further, it enables efficient ...
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作者：Dubey, Paromita; Mueller, Hans-Georg
作者单位：University of Southern California; University of California System; University of California Davis
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作者：Cai, Tianxi; Cai, T. Tony; Guo, Zijian
作者单位：Harvard University; University of Pennsylvania; Rutgers University System; Rutgers University New Brunswick
摘要：The ability to predict individualized treatment effects (ITEs) based on a given patient's profile is essential for personalized medicine. We propose a hypothesis testing approach to choosing between two potential treatments for a given individual in the framework of high-dimensional linear models. The methodological novelty lies in the construction of a debiased estimator of the ITE and establishment of its asymptotic normality uniformly for an arbitrary future high-dimensional observation, wh...
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作者：Lavancier, Frederic; Le Guevel, Ronan
作者单位：Nantes Universite; Universite de Rennes; Centre National de la Recherche Scientifique (CNRS)
摘要：Many spatiotemporal data record the time of birth and death of individuals, along with their spatial trajectories during their lifetime, whether through continuous-time observations or discrete-time observations. Natural applications include epidemiology, individual-based modelling in ecology, spatiotemporal dynamics observed in bioimaging and computer vision. The aim of this article is to estimate in this context the birth and death intensity functions that depend in full generality on the cu...
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作者：Heller; Rosset
