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最新文章

• SEQUENTIAL SAMPLING IN PROSPECTIVE OBSERVATIONAL STUDIES AI翻译
  作者：Ryan, Mary M.; Gillen, Daniel L.
  作者单位：University of California System; University of California Irvine
  摘要：Many factors must be taken into account when designing an observa-tional study. Unlike controlled studies, observational studies cannot mitigate the effects of confounding through randomization, and such factors should be incorporated into both the study analysis and the study design. Unfortu-nately, there is often little data available on most of these factors at the design stage, rendering it infeasible to reliably postulate the impact of these fac-tors on the treatment effect estimate and p...
• SOCIAL DISTANCING AND COVID-19: RANDOMIZATION INFERENCE FOR A STRUCTURED DOSE-RESPONSE RELATIONSHIP AI翻译
  作者：Zhang, Bo; Heng, Siyu; Ye, Ting; Small, Dylan S.
  作者单位：University of Pennsylvania; University of Pennsylvania; University of Washington; University of Washington Seattle
  摘要：Social distancing is widely acknowledged as an effective public health policy combating the novel coronavirus. But extreme forms of social distancing, like isolation and quarantine, have costs, and it is not clear how much social distancing is needed to achieve public health effects. In this article we develop a design-based framework to test the causal null hypothesis and make inference about the dose-response relationship between reduction in social mobility and COVID-19 related public healt...
• HANDLING CATEGORICAL FEATURES WITH MANY LEVELS USING A PRODUCT PARTITION MODEL AI翻译
  作者：Criscuolo, Tulio L.; Assuncao, Renato M.; Loschi, Rosangela H.; Meira Jr, Wagner; Cruz-Reyes, Danna
  作者单位：Universidade Federal de Minas Gerais; Environmental Systems Research Institute, Inc. (ESRI); Universidade Federal de Minas Gerais; National University of Rosario
  摘要：A common difficulty in data analysis is how to handle categorical predictors with a large number of levels or categories. Few proposals have been developed to tackle this important and frequent problem. We introduce a generative model that simultaneously carries out the model fitting and the aggregation of the categorical levels into larger groups. We represent the categorical predictor by a graph where the nodes are the categories and establish a probability distribution over meaningful parti...
• INDIVIDUALIZED RISK ASSESSMENT OF PREOPERATIVE OPIOID USE BY INTERPRETABLE NEURAL NETWORK REGRESSION AI翻译
  作者：Sun, Yuming; Kang, Jian; Brummett, Chad; Li, Yi
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Preoperative opioid use has been reported to be associated with higher preoperative opioid demand, worse postoperative outcomes, and increased postoperative healthcare utilization and expenditures. Understanding the risk of preoperative opioid use helps establish patient-centered pain management. In the field of machine learning, deep neural network (DNN) has emerged as a powerful means for risk assessment because of its superb prediction power; however, the blackbox algorithms may make the re...
• ESTIMATING PROMOTION EFFECTS IN EMAIL MARKETING USING A LARGE-SCALE CROSS-CLASSIFIED BAYESIAN JOINT MODEL FOR NESTED IMBALANCED DATA AI翻译
  作者：Mukhopadhyay, Sabyasachi; Kar, Wreetabrata; Mukherjee, Gourab
  作者单位：Indian Institute of Management (IIM System); Indian Institute of Management Bangalore; Purdue University System; Purdue University; University of Southern California
  摘要：We consider a large-scale, cross-classified nested (CRON) joint model for modeling customer responses to opening, clicking, and purchasing from promotion emails. Our logistic regression-based joint model contains cross -ing of promotions and customer effects and allows estimation of the hetero-geneous effects of different promotion emails, after adjusting for customer preferences, attributes, and historical behaviors. Using data from an email marketing campaign of an apparel retailer, we exhib...
• ALPHA: AUDIT THAT LEARNS FROM PREVIOUSLY HAND-AUDITED BALLOTS AI翻译
  作者：Stark, Philip B.
  作者单位：University of California System; University of California Berkeley
  摘要：A risk-limiting election audit (RLA) offers a statistical guarantee: if the reported electoral outcome is incorrect, the audit has a known maximum chance (the risk limit) of not correcting it before it becomes final. BRAVO (Lindeman, Stark and Yates (In Proceedings of the 2011 Electronic Voting Technology Workshop/Workshop on Trustworthy Elections (EVT/WOTE'11) (2012) USENIX)), based on Wald's sequential probability ratio test for the Bernoulli parameter, is the simplest and most widely tried ...
• A VARIATIONAL BAYESIAN APPROACH TO IDENTIFYING WHOLE-BRAIN DIRECTED NETWORKS WITH FMRI DATA AI翻译
  作者：Wang, Yaotian; Yan, Guofen; Wang, Xiaofeng; LI, Shuoran; Peng, Lingyi; Tudorascu, Dana L.; Zhang, Tingting
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Virginia; Cleveland Clinic Foundation; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：The brain is a high-dimensional directed network system, as it consists of many regions as network nodes that exert influence on each other. The directed influence exerted by one region on another is referred to as directed connectivity. We aim to reveal whole-brain directed networks based on resting-state functional magnetic resonance imaging (fMRI) data of many subjects. However, it is both statistically and computationally challenging to produce scientifically meaningful estimates of whole-...
• MODELING A NONLINEAR BIOPHYSICAL TREND FOLLOWED BY LONG-MEMORY EQUILIBRIUM WITH UNKNOWN CHANGE POINT AI翻译
  作者：Zhang, Wenyu; Griffin, Maryclare; Matteson, David S.
  作者单位：Cornell University; University of Massachusetts System; University of Massachusetts Amherst
  摘要：Measurements of many biological processes are characterized by an ini-tial trend period followed by an equilibrium period. Scientists may wish to quantify features of the two periods as well as the timing of the change point. Specifically, we are motivated by problems in the study of electrical cell -substrate impedance sensing (ECIS) data. ECIS is a popular new technology which measures cell behavior noninvasively. Previous studies using ECIS data have found that different cell types can be c...
• BAYESIAN NON-HOMOGENEOUS HIDDEN MARKOV MODEL WITH VARIABLE SELECTION FOR INVESTIGATING DRIVERS OF SEIZURE RISK CYCLING AI翻译
  作者：Wang, Emily T.; Chiang, Sharon; Haneef, Zulfi; Rao, Vikram R.; Moss, Robert; Vannucci, Marina
  作者单位：Rice University; University of California System; University of California San Francisco; Baylor College of Medicine
  摘要：A major issue in the clinical management of epilepsy is the unpredictabil-ity of seizures. Yet, traditional approaches to seizure forecasting and risk assessment in epilepsy rely heavily on raw seizure frequencies which are a stochastic measurement of seizure risk. We consider a Bayesian nonhomo-geneous hidden Markov model for unsupervised clustering of zero-inflated seizure count data. The proposed model allows for a probabilistic estimate of the sequence of seizure risk states at the individ...