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作者：Da Silva, D. N.; Skinner, C. J.
作者单位：University of London; London School Economics & Political Science
摘要：Paradata refers to survey variables which are not of direct interest themselves, but are related to the quality of data on survey variables which are of interest. We focus on a categorical paradata variable, which reflects the presence of measurement error in a variable of interest. We propose a quasi-score test of the hypothesis of no measurement error bias in the estimation of regression coefficients under models for paradata. We also propose a regression-based test, analogous to a simple te...
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作者：Kuffner, T. A.; Lee, S. M. S.; Young, G. A.
作者单位：Washington University (WUSTL); University of Hong Kong; Imperial College London
摘要：We establish a general theory of optimality for block bootstrap distribution estimation for sample quantiles under mild strong mixing conditions. In contrast to existing results, we study the block bootstrap for varying numbers of blocks. This corresponds to a hybrid between the subsampling bootstrap and the moving block bootstrap, in which the number of blocks is between 1 and the ratio of sample size to block length. The hybrid block bootstrap is shown to give theoretical benefits, and start...
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作者：Nie, X.; Wager, S.
作者单位：Stanford University; Stanford University
摘要：Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical applications, such as personalized medicine and optimal resource allocation. In this article we develop a general class of two-step algorithms for heterogeneous treatment effect estimation in observational studies. First, we estimate marginal effects and treatment propensities to form an objective function that isolates the causal component of the signal. Then, we optimize this data-adaptive objective ...
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作者：Fang, Junhan; Yi, Grace Y.
作者单位：University of Waterloo; Western University (University of Western Ontario)
摘要：Measurement error in covariates has been extensively studied in many conventional regression settings where covariate information is typically expressed in a vector form. However, there has been little work on error-prone matrix-variate data, which commonly arise from studies with imaging, spatial-temporal structures, etc. We consider analysis of error-contaminated matrix-variate data. We particularly focus on matrix-variate logistic measurement error models. We examine the biases induced from...
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作者：Rotnitzky, A.; Smucler, E.; Robins, J. M.
作者单位：Universidad Torcuato Di Tella; Universidad Torcuato Di Tella; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We study a class of parameters with the so-called mixed bias property. For parameters with this property, the bias of the semiparametric efficient one-step estimator is equal to the mean of the product of the estimation errors of two nuisance functions. In nonparametric models, parameters with the mixed bias property admit so-called rate doubly robust estimators, i.e., estimators that are consistent and asymptotically normal when one succeeds in estimating both nuisance functions at sufficient...
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作者：Wang, Shulei; Cai, T. Tony; Li, Hongzhe
作者单位：University of Pennsylvania; University of Pennsylvania
摘要：Quantitative comparison of microbial composition from different populations is a fundamental task in various microbiome studies. We consider two-sample testing for microbial compositional data by leveraging phylogenetic information. Motivated by existing phylogenetic distances, we take a minimum-cost flow perspective to study such testing problems. We first show that multivariate analysis of variance with permutation using phylogenetic distances, one of the most commonly used methods in practi...
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作者：Zhang, Ting
作者单位：Boston University
摘要：Quantile regression is a popular and powerful method for studying the effect of regressors on quantiles of a response distribution. However, existing results on quantile regression were mainly developed for cases in which the quantile level is fixed, and the data are often assumed to be independent. Motivated by recent applications, we consider the situation where (i) the quantile level is not fixed and can grow with the sample size to capture the tail phenomena, and (ii) the data are no longe...
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作者：Diaz, I; Hejazi, N. S.; Rudolph, K. E.; van der Laan, M. J.
作者单位：Cornell University; Weill Cornell Medicine; University of California System; University of California Berkeley; Columbia University
摘要：Interventional effects for mediation analysis were proposed as a solution to the lack of identifiability of natural (in)direct effects in the presence of a mediator-outcome confounder affected by exposure. We present a theoretical and computational study of the properties of the interventional (in)direct effect estimands based on the efficient influence function in the nonparametric statistical model. We use the efficient influence function to develop two asymptotically optimal nonparametric e...
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作者：Hazelton, M. L.; Mcveagh, M. R.; van Brunt, B.
作者单位：University of Otago; Massey University
摘要：For statistical linear inverse problems involving count data, inference typically requires sampling a latent variable with conditional support comprising of the lattice points in a convex polytope. Irreducibility of random walk samplers is guaranteed only if a sufficiently rich array of sampling directions is available. In principle, this can be achieved by finding a Markov basis of moves ab initio, but in practice doing so may be computationally infeasible. What is more, the use of a full Mar...
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作者：Li, Wenlong; Liu, Min-Qian; Tang, Boxin
作者单位：Nankai University; Simon Fraser University
摘要：An attractive type of space-filling design for computer experiments is the class of maximin distance designs. Algorithmic search is commonly used for finding such designs, but this approach becomes ineffective for large problems. Theoretical construction of maximin distance designs is challenging; some results have been obtained recently, often using highly specialized techniques. This article presents an easy-to-use method for constructing maximin distance designs. The method is versatile as ...
