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作者：Jin, Ying; Rothenhaeusler, Dominik
作者单位：Stanford University
摘要：Parameters of subpopulations can be more relevant than those of superpopulations. For example, a healthcare provider may be interested in the effect of a treatment plan for a specific subset of their patients; policymakers may be concerned with the impact of a policy in a particular state within a given population. In these cases, the focus is on a specific finite population, as opposed to an infinite superpopulation. Such a population can be characterized by fixing some attributes that are in...
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作者：Zhang, Yao; Zhao, Qingyuan
作者单位：Stanford University; University of Cambridge
摘要：We consider the problem of constructing multiple independent conditional randomization tests using a single dataset. Because the tests are independent, the randomization p-values can be interpreted individually and combined using standard methods for multiple testing. We give a simple, sequential construction of such tests and then discuss its application to three problems: Rosenbaum's evidence factors for observational studies, lagged treatment effects in stepped-wedge trials, and spillover e...
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作者：Aue, Alexander; Kirch, Claudia
作者单位：University of California System; University of California Davis; Otto von Guericke University
摘要：Quality control charts aim at raising an alarm as soon as sequentially obtained observations of an underlying random process no longer seem to be within stochastic fluctuations prescribed by an in-control scenario. Such random processes can often be modelled using the concept of stationarity, or even independence as in most classical works. An important out-of-control scenario is the changepoint alternative, for which the distribution of the process changes at an unknown point in time. In his ...
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作者：Cui, Y.; Tchetgen, E. J. Tchetgen
作者单位：Zhejiang University; Zhejiang University; University of Pennsylvania
摘要：While model selection is a well-studied topic in parametric and nonparametric regression or density estimation, selection of possibly high-dimensional nuisance parameters in semiparametric problems is far less developed. In this paper, we propose a selective machine learning framework for making inferences about a finite-dimensional functional defined on a semiparametric model, when the latter admits a doubly robust estimating function and several candidate machine learning algorithms are avai...
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作者：Cohen, P. L.; Fogarty, C. B.
作者单位：Massachusetts Institute of Technology (MIT); University of Michigan System; University of Michigan
摘要：In randomized experiments, adjusting for observed features when estimating treatment effects has been proposed as a way to improve asymptotic efficiency. However, among parametric methods, only linear regression has been proven to form an estimate of the average treatment effect that is asymptotically no less efficient than the treated-minus-control difference in means regardless of the true data generating process. Randomized treatment assignment provides this do-no-harm property, with neithe...
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作者：Qu, Lianqiang; Sun, Liuquan; Sun, Yanqing
作者单位：Central China Normal University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of North Carolina; University of North Carolina Charlotte
摘要：Quantile regression has become a widely used tool for analysing competing risk data. However, quantile regression for competing risk data with a continuous mark is still scarce. The mark variable is an extension of cause of failure in a classical competing risk model where cause of failure is replaced by a continuous mark only observed at uncensored failure times. An example of the continuous mark variable is the genetic distance that measures dissimilarity between the infecting virus and the ...
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作者：Mccloskey, A.
作者单位：University of Colorado System; University of Colorado Boulder
摘要：I propose a new type of confidence interval for correct asymptotic inference after using data to select a model of interest without assuming any model is correctly specified. This hybrid confidence interval is constructed by combining techniques from the selective inference and post-selection inference literatures to yield a short confidence interval across a wide range of data realizations. I show that hybrid confidence intervals have correct asymptotic coverage, uniformly over a large class ...
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作者：Luo, Lan; Wang, Jingshen; Hector, Emily C.
作者单位：University of Iowa; University of California System; University of California Berkeley; North Carolina State University
摘要：Modern longitudinal data, for example from wearable devices, may consist of measurements of biological signals on a fixed set of participants at a diverging number of time-points. Traditional statistical methods are not equipped to handle the computational burden of repeatedly analysing the cumulatively growing dataset each time new data are collected. We propose a new estimation and inference framework for dynamic updating of point estimates and their standard errors along sequentially collec...
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作者：Guo, F. Richard; Perkovic, Emilija; Rotnitzky, Andrea
作者单位：University of Cambridge; University of Washington; University of Washington Seattle; Universidad Torcuato Di Tella
摘要：We study efficient estimation of an interventional mean associated with a point exposure treatment under a causal graphical model represented by a directed acyclic graph without hidden variables. Under such a model, a subset of the variables may be uninformative, in that failure to measure them neither precludes identification of the interventional mean nor changes the semiparametric variance bound for regular estimators of it. We develop a set of graphical criteria that are sound and complete...
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作者：Yu, Haihan; Kaiser, Mark S.; Nordman, Daniel J.
作者单位：Iowa State University
摘要：Bootstrapping spectral mean statistics has been a notoriously difficult problem over the past 25 years. Many frequency domain bootstraps are valid only for certain time series structures, e.g., linear processes, or for special types of statistics, i.e., ratio statistics, because such bootstraps fail to capture the limiting variance of spectral statistics in general settings. We address this issue with a different form of resampling, namely, subsampling. While not considered previously, subsamp...
