Journal of the American Statistical Association

最新文章

• Topic Modeling on Triage Notes With Semiorthogonal Nonnegative Matrix Factorization AI翻译
  作者：Li, Yutong; Zhu, Ruoqing; Qu, Annie; Ye, Han; Sun, Zhankun
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of California System; University of California Irvine; University of Illinois System; University of Illinois Urbana-Champaign; City University of Hong Kong
  摘要：Emergency department (ED) crowding is a universal health issue that affects the efficiency of hospital management and patient care quality. ED crowding frequently occurs when a request for a ward-bed for a patient is delayed until a doctor makes an admission decision. In this case study, we build a classifier to predict the disposition of patients using manually typed nurse notes collected during triage as provided by the Alberta Medical Center. These predictions can potentially be incorporate...
• Extreme and Inference for Tail Gini Functionals With Applications in Tail Risk Measurement AI翻译
  作者：Hou, Yanxi; Wang, Xing
  作者单位：Fudan University; Illinois Institute of Technology
  摘要：Tail risk analysis focuses on the problem of risk measurement on the tail regions of financial variables. As one crucial task in tail risk analysis for risk management, the measurement of tail risk variability is less addressed in the literature. Neither the theoretical results nor inference methods are fully developed, which results in the difficulty of modeling implementation. Practitioners are then short of measurement methods to understand and evaluate tail risks, even when they have large...
• Prediction Intervals for Synthetic Control Methods AI翻译
  作者：Cattaneo, Matias D.; Feng, Yingjie; Titiunik, Rocio
  作者单位：Princeton University; Tsinghua University; Princeton University
  摘要：Uncertainty quantification is a fundamental problem in the analysis and interpretation of synthetic control (SC) methods. We develop conditional prediction intervals in the SC framework, and provide conditions under which these intervals offer finite-sample probability guarantees. Our method allows for covariate adjustment and nonstationary data. The construction begins by noting that the statistical uncertainty of the SC prediction is governed by two distinct sources of randomness: one coming...
• Advanced Survival Models AI翻译
  作者：Kang, Sangwook
  作者单位：Yonsei University
• Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data AI翻译
  作者：Quick, Corbin; Dey, Rounak; Lin, Xihong
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University
  摘要：Modeling infectious disease dynamics has been critical throughout the COVID-19 pandemic. Of particular interest are the incidence, prevalence, and effective reproductive number (R-t). Estimating these quantities is challenging due to under-ascertainment, unreliable reporting, and time lags between infection, onset, and testing. We propose a Multilevel Epidemic Regression Model to Account for Incomplete Data (MERMAID) to jointly estimate R-t, ascertainment rates, incidence, and prevalence over ...
• Matrix Completion Methods for Causal Panel Data Models AI翻译
  作者：Athey, Susan; Bayati, Mohsen; Doudchenko, Nikolay; Imbens, Guido; Khosravi, Khashayar
  作者单位：Stanford University; National Bureau of Economic Research; Stanford University; Stanford University; Stanford University
  摘要：In this article, we study methods for estimating causal effects in settings with panel data, where some units are exposed to a treatment during some periods and the goal is estimating counterfactual (untreated) outcomes for the treated unit/period combinations. We propose a class of matrix completion estimators that uses the observed elements of the matrix of control outcomes corresponding to untreated unit/periods to impute the missing elements of the control outcome matrix, corresponding to ...
• Design of experiments for generalized linear models AI翻译
  作者：Choe, Youngjun
  作者单位：University of Washington; University of Washington Seattle
• Brain Regions Identified as Being Associated With Verbal Reasoning Through the Use of Imaging Regression via Internal Variation AI翻译
  作者：Feng, Long; Bi, Xuan; Zhang, Heping
  作者单位：Yale University; University of Minnesota System; University of Minnesota Twin Cities
  摘要：Brain-imaging data have been increasingly used to understand intellectual disabilities. Despite significant progress in biomedical research, the mechanisms for most of the intellectual disabilities remain unknown. Finding the underlying neurological mechanisms has proved difficult, especially in children due to the rapid development of their brains. We investigate verbal reasoning, which is a reliable measure of an individual's general intellectual abilities, and develop a class of high-order ...
• Doubly Robust Estimation of Optimal Dosing Strategies AI翻译
  作者：Schulz, Juliana; Moodie, Erica E. M.
  作者单位：Universite de Montreal; HEC Montreal; McGill University
  摘要：The goal of precision medicine is to tailor treatment strategies on an individual patient level. Although several estimation techniques have been developed for determining optimal treatment rules, the majority of methods focus on the case of a dichotomous treatment, an example being the dynamic weighted ordinary least squares regression approach of Wallace and Moodie. We propose an extension to the aforementioned framework to allow for a continuous treatment with the ultimate goal of estimatin...
• Regression Modeling for Size-and-Shape Data Based on a Gaussian Model for Landmarks AI翻译
  作者：Dryden, Ian L.; Kume, Alfred; Paine, Phillip J.; Wood, Andrew T. A.
  作者单位：University of Nottingham; University of Kent; University of Sheffield; Australian National University
  摘要：In this article, we propose a regression model for size-and-shape response data. So far as we are aware, few such models have been explored in the literature to date. We assume a Gaussian model for labeled landmarks; these landmarks are used to represent the random objects under study. The regression structure, assumed in this article to be linear in the ambient space, enters through the landmark means. Two approaches to parameter estimation are considered. The first approach is based directly...