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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,...
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作者：Yang, Tao; Huang, Ying; Fong, Youyi
作者单位：Fred Hutchinson Cancer Center
摘要：We consider the use of threshold-based regression models to evaluate immune response biomarkers as principal surrogate markers of a vaccine's protective effect. Threshold-based regression models, which allow the relationship between a clinical outcome and a covariate to change dramatically across a threshold value in the covariate, have been studied by various authors under fully observed data. Limited research, however, has examined these models in the presence of missing covariates, such as ...
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作者：Van den Boom, W.; Reeves, G.; Dunson, D. B.
作者单位：Yale NUS College; National University of Singapore; Duke University
摘要：Posterior computation for high-dimensional data with many parameters can be challenging. This article focuses on a new method for approximating posterior distributions of a low- to moderate-dimensional parameter in the presence of a high-dimensional or otherwise computationally challenging nuisance parameter. The focus is on regression models and the key idea is to separate the likelihood into two components through a rotation. One component involves only the nuisance parameters, which can the...
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作者：Zheng, Yao; Cheng, Guang
作者单位：University of Connecticut; Purdue University System; Purdue University
摘要：This paper develops a unified finite-time theory for the ordinary least squares estimation of possibly unstable and even slightly explosive vector autoregressive models under linear restrictions, with the applicable region rho(A) <= 1 + c/n, where rho(A) is the spectral radius of the transition matrix A in the VAR(1) representation, n is the time horizon and c > 0 is a universal constant. The linear restriction framework encompasses various existing models such as banded/network vector autoreg...
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作者：Guo, F. Richard; Richardson, Thomas S.; Robins, James M.
作者单位：University of Washington; University of Washington Seattle; Harvard University; Harvard T.H. Chan School of Public Health
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作者：Jeong, Seonghyun; Ghosal, Subhashis
作者单位：Yonsei University; North Carolina State University
摘要：We study posterior contraction rates in sparse high-dimensional generalized linear models using priors incorporating sparsity. A mixture of a point mass at zero and a continuous distribution is used as the prior distribution on regression coefficients. In addition to the usual posterior, the fractional posterior, which is obtained by applying Bayes theorem with a fractional power of the likelihood, is also considered. The latter allows uniformity in posterior contraction over a larger subset o...
