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作者：Heinrich, Claudio; Hellton, Kristoffer H.; Lenkoski, Alex; Thorarinsdottir, Thordis L.
摘要：Seasonal weather forecasts are crucial for long-term planning in many practical situations and skillful forecasts may have substantial economic and humanitarian implications. Current seasonal forecasting models require statistical postprocessing of the output to correct systematic biases and unrealistic uncertainty assessments. We propose a multivariate postprocessing approach using covariance tapering, combined with a dimension reduction step based on principal component analysis for efficien...
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作者：Nattino, Giovanni; Lu, Bo; Shi, Junxin; Lemeshow, Stanley; Xiang, Henry
作者单位：University System of Ohio; Ohio State University; University System of Ohio; Ohio State University; Nationwide Childrens Hospital; Research Institute at Nationwide Children's Hospital; University System of Ohio; Ohio State University
摘要：Comparing outcomes across different levels of trauma centers is vital in evaluating regionalized trauma care. With observational data, it is critical to adjust for patient characteristics to render valid causal comparisons. Propensity score matching is a popular method to infer causal relationships in observational studies with two treatment arms. Few studies, however, have used matching designs with more than two groups, due to the complexity of matching algorithms. We fill the gap by develop...
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作者：Yan, Bowei; Sarkar, Purnamrita
作者单位：University of Texas System; University of Texas Austin
摘要：In this article, we investigate community detection in networks in the presence of node covariates. In many instances, covariates and networks individually only give a partial view of the cluster structure. One needs to jointly infer the full cluster structure by considering both. In statistics, an emerging body of work has been focused on combining information from both the edges in the network and the node covariates to infer community memberships. However, so far the theoretical guarantees ...
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作者：Dean, Natalie; Yang, Yang
作者单位：Emory University; State University System of Florida; University of Florida
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作者：[Anonymous]
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作者：Hiabu, Munir; Mammen, Enno; Dolores Martinez-Miranda, M.; Nielsen, Jens P.
作者单位：University of Sydney; Ruprecht Karls University Heidelberg; University of Granada; City St Georges, University of London
摘要：Smooth backfitting has proven to have a number of theoretical and practical advantages in structured regression. By projecting the data down onto the structured space of interest smooth backfitting provides a direct link between data and estimator. This article introduces the ideas of smooth backfitting to survival analysis in a proportional hazard model, where we assume an underlying conditional hazard with multiplicative components. We develop asymptotic theory for the estimator. In a compre...
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作者：Martinez, Wendy L.
摘要：Each year, the Journal of the American Statistical Association (ASA) publishes the presidential address from the Joint Statistical Meetings (JSM). Here, we present the 2020 address verbatim save for the addition of references and a few minor editorial corrections.
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作者：Sun, Yifei; McCulloch, Charles E.; Marr, Kieren A.; Huang, Chiung-Yu
作者单位：Columbia University; University of California System; University of California San Francisco; Johns Hopkins University
摘要：Although increasingly used as a data resource for assembling cohorts, electronic health records (EHRs) pose many analytic challenges. In particular, a patient's health status influences when and what data are recorded, generating sampling bias in the collected data. In this article, we consider recurrent event analysis using EHR data. Conventional regression methods for event risk analysis usually require the values of covariates to be observed throughout the follow-up period. In EHR databases...
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作者：Liang, Decai; Zhang, Haozhe; Chang, Xiaohui; Huang, Hui
作者单位：Peking University; Peking University; Nankai University; Microsoft; Oregon State University; Sun Yat Sen University
摘要：Severe air pollution affects billions of people around the world, particularly in developing countries such as China. Effective emission control policies rely primarily on a proper assessment of air pollutants and accurate spatial clustering outcomes. Unfortunately, emission patterns are difficult to observe as they are highly confounded by many meteorological and geographical factors. In this study, we propose a novel approach for modeling and clustering PM2.5 concentrations across China. We ...
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作者：Ertefaie, Ashkan; McKay, James R.; Oslin, David; Strawderman, Robert L.
作者单位：University of Rochester; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania
摘要：Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically used to estimate certain nuisance parameters, and misspecification of these working models can result in residual confounding and/or efficiency loss. We propose a robust Q-learning approach which allows estimating such nuisance parameters using data-adaptive techniques. We study the asymptotic behavior of our estima...
