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作者：James, Gareth M.; Paulso, Courtney; Rusmevichientong, Paat
作者单位：University of Southern California; University System of Maryland; University of Maryland College Park
摘要：Firms are increasingly transitioning advertising budgets to Internet display campaigns, but this transition poses new challenges. These campaigns use numerous potential metrics for success (e.g., reach or click rate), and because each website represents a separate advertising opportunity, this is also an inherently high-dimensional problem. Further, advertisers often have constraints they wish to place on their campaign, such as targeting specific sub-populations or websites. These challenges ...
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作者：Jacob, Pierre E.; Lindsten, Fredrik; Schon, Thomas B.
作者单位：Harvard University; Linkoping University; Uppsala University
摘要：In state-space models, smoothing refers to the task of estimating a latent stochastic process given noisy measurements related to the process. We propose an unbiased estimator of smoothing expectations. The lack-of-bias property has methodological benefits: independent estimators can be generated in parallel, and CI can be constructed from the central limit theorem to quantify the approximation error. To design unbiased estimators, we combine a generic debiasing technique for Markov chains, wi...
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作者：Song, Hyebin; Raskutti, Garvesh
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：In various real-world problems, we are presented with classification problems with positive and unlabeled data, referred to as presence-only responses. In this article we study variable selection in the context of presence only responses where the number of features or covariates p is large. The combination of presence-only responses and high dimensionality presents both statistical and computational challenges. In this article, we develop the PUlasso algorithm for variable selection and class...
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作者：Ando, Tomohiro; Bai, Jushan
作者单位：University of Melbourne; Columbia University; Nankai University
摘要：This article introduces a new procedure for analyzing the quantile co-movement of a large number of financial time series based on a large-scale panel data model with factor structures. The proposed method attempts to capture the unobservable heterogeneity of each of the financial time series based on sensitivity to explanatory variables and to the unobservable factor structure. In our model, the dimension of the common factor structure varies across quantiles, and the explanatory variables is...
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作者：Adhikari, Samrachana; Rose, Sherri; Normand, Sharon-Lise
作者单位：New York University; Harvard University; Harvard Medical School; Harvard University; Harvard T.H. Chan School of Public Health
摘要：Percutaneous coronary interventions (PCIs) are nonsurgical procedures to open blocked blood vessels to the heart, frequently using a catheter to place a stent. The catheter can be inserted into the blood vessels using an artery in the groin or an artery in the wrist. Because clinical trials have indicated that access via the wrist may result in fewer post procedure complications, shortening the length of stay, and ultimately cost less than groin access, adoption of access via the wrist has bee...
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作者：Lin, Ruitao; Thall, Peter F.; Yuan, Ying
作者单位：University of Texas System; UTMD Anderson Cancer Center
摘要：A Bayesian group sequential design is proposed that performs survival comparisons within patient subgroups in randomized trials where treatment-subgroup interactions may be present. A latent subgroup membership variable is assumed to allow the design to adaptively combine homogeneous subgroups, or split heterogeneous subgroups, to improve the procedure's within-subgroup power. If a baseline covariate related to survival is available, the design may incorporate this information to improve subgr...
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作者：Yadlowsky, Steve; Pellegrini, Fabio; Lionetto, Federica; Braune, Stefan; Tian, Lu
作者单位：Stanford University; Stanford University
摘要：While sample sizes in randomized clinical trials are large enough to estimate the average treatment effect well, they are often insufficient for estimation of treatment-covariate interactions critical to studying data-driven precision medicine. Observational data from real world practice may play an important role in alleviating this problem. One common approach in trials is to predict the outcome of interest with separate regression models in each treatment arm, and estimate the treatment eff...
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作者：Xie, Min-ge; Zheng, Zheshi
作者单位：Rutgers University System; Rutgers University New Brunswick
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作者：Vatter, Thibault
作者单位：Columbia University
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作者：Rashid, Nairn U.; Li, Quefeng; Yeh, Jen Jen; Ibrahim, Joseph G.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene sign...
