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作者：Gunsilius, F. F.
作者单位：University of Michigan System; University of Michigan
摘要：This note presents a proof of the conjecture in Pearl (1995) about testing the validity of an instrumental variable in hidden variable models. It implies that instrument validity cannot be tested in the case where the endogenous treatment is continuously distributed. This stands in contrast to the classical testability results for instrument validity when the treatment is discrete. However, imposing weak structural assumptions on the model, such as continuity between the observable variables, ...
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作者：Plumlee, M.; Erickson, C. B.; Ankenman, B. E.; Lawrence, E.
作者单位：Northwestern University; United States Department of Energy (DOE); Los Alamos National Laboratory
摘要：Experiments are often used to produce emulators of deterministic computer code. This article introduces composite grid experimental designs and a sequential method for building the designs for accurate emulation. Computational methods are developed that enable fast and exact Gaussian process inference even with large sample sizes. We demonstrate that the proposed approach can produce emulators that are orders of magnitude more accurate than current approximations at a comparable computational ...
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作者：Lei, Lihua; Bickel, Peter J.
作者单位：Stanford University; University of California System; University of California Berkeley
摘要：We propose the cyclic permutation test to test general linear hypotheses for linear models. The test is nonrandomized and valid in finite samples with exact Type I error a for an arbitrary fixed design matrix and arbitrary exchangeable errors, whenever 1/alpha is an integer and n/p >= 1/alpha - 1, where n is the sample size and p is the number of parameters. The test involves applying the marginal rank test to 1/alpha linear statistics of the outcome vector, where the coefficient vectors are d...
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作者：Zhou, Huijuan; Zhang, Xianyang; Chen, Jun
作者单位：Renmin University of China; Texas A&M University System; Texas A&M University College Station; Mayo Clinic
摘要：The familywise error rate has been widely used in genome-wide association studies. With the increasing availability of functional genomics data, it is possible to increase detection power by leveraging these genomic functional annotations. Previous efforts to accommodate covariates in multiple testing focused on false discovery rate control, while covariate-adaptive procedures controlling the familywise error rate remain underdeveloped. Here, we propose a novel covariate-adaptive procedure to ...
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作者：Guo, X.; Tang, C. Y.
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：We consider testing the covariance structure in statistical models. We focus on developing such tests when the random vectors of interest are not directly observable and have to be derived via estimated models. Additionally, the covariance specification may involve extra nuisance parameters which also need to be estimated. In a generic additive model setting, we develop and investigate test statistics based on the maximum discrepancy measure calculated from the residuals. To approximate the di...
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作者：Howard, S. R.; Pimentel, S. D.
作者单位：University of California System; University of California Berkeley
摘要：A sensitivity analysis in an observational study tests whether the qualitative conclusions of an analysis would change if we were to allow for the possibility of limited bias due to confounding. The design sensitivity of a hypothesis test quantifies the asymptotic performance of the test in a sensitivity analysis against a particular alternative. We propose a new, nonasymptotic, distribution-free test, the uniform general signed rank test, for observational studies with paired data, and examin...
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作者：Ma, Huijuan; Peng, Limin; Huang, Chiung-Yu; Fu, Haoda
作者单位：East China Normal University; Emory University; University of California System; University of California San Francisco; Eli Lilly; Lilly Research Laboratories
摘要：Progression of chronic disease is often manifested by repeated occurrences of disease-related events over time. Delineating the heterogeneity in the risk of such recurrent events can provide valuable scientific insight for guiding customized disease management. We propose a new sensible measure of individual risk of recurrent events and present a dynamic modelling framework thereof, which accounts for both observed covariates and unobservable frailty. The proposed modelling requires no distrib...
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作者：Bubenik, Peter
作者单位：State University System of Florida; University of Florida
摘要：Garside et al. (2021) use event history methods to analyse topological data. We provide additional background on persistent homology to contrast the hazard estimators used in Garside et al. (2021) with standard approaches in topological data analysis. In particular, Garside et al.'s approach is a local method, which has advantages and disadvantages, whereas homology is global. We also provide more details on persistence landscapes and show how a more complete use of this statistic improves its...
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作者：Zeng, Donglin; Lin, D. Y.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：Panel count data, in which the observation for each study subject consists of the number of recurrent events between successive examinations, are commonly encountered in industrial reliability testing, medical research and other scientific investigations. We formulate the effects of potentially time-dependent covariates on one or more types of recurrent events through nonhomogeneous Poisson processes with random effects. We employ nonparametric maximum likelihood estimation under arbitrary exa...
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作者：Ma, Rong; Barnett, Ian
作者单位：University of Pennsylvania
摘要：Modularity is a popular metric for quantifying the degree of community structure within a network. The distribution of the largest eigenvalue of a network's edge weight or adjacency matrix is well studied and is frequently used as a substitute for modularity when performing statistical inference. However, we show that the largest eigenvalue and modularity are asymptotically uncorrelated, which suggests the need for inference directly on modularity itself when the network is large. To this end,...
