Journal of the American Statistical Association

最新文章

• Quantile Co-Movement in Financial Markets: A Panel Quantile Model With Unobserved Heterogeneity AI翻译
  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...
• Nonparametric Bayesian Instrumental Variable Analysis: Evaluating Heterogeneous Effects of Coronary Arterial Access Site Strategies AI翻译
  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...
• BAGS: A Bayesian Adaptive Group Sequential Trial Design With Subgroup-Specific Survival Comparisons AI翻译
  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...
• Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data AI翻译
  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...
• Discussion of Professor Bradley Efron's Article on Prediction, Estimation, and Attribution AI翻译
  作者：Xie, Min-ge; Zheng, Zheshi
  作者单位：Rutgers University System; Rutgers University New Brunswick
• Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications, 2nd edition AI翻译
  作者：Vatter, Thibault
  作者单位：Columbia University
• Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction AI翻译
  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...
• Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications AI翻译
  作者：Chen, Yunxiao; Li, Xiaoou; Zhang, Siliang
  作者单位：University of London; London School Economics & Political Science; University of Minnesota System; University of Minnesota Twin Cities; Fudan University
• Theory of Spatial Statistics: A Concise Introduction AI翻译
  作者：Schoenberg, Frederic P.
  作者单位：University of California System; University of California Los Angeles
• From Fixed-X to Random-X Regression: Bias-Variance Decompositions, Covariance Penalties, and Prediction Error Estimation: Rejoinder AI翻译
  作者：Rosset, Saharon; Tibshirani, Ryan J.
  作者单位：Tel Aviv University; Carnegie Mellon University; Carnegie Mellon University