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• BOUNDING THE LOCAL AVERAGE TREATMENT EFFECT IN AN INSTRUMENTAL VARIABLE ANALYSIS OF ENGAGEMENT WITH A MOBILE INTERVENTION AI翻译
  作者：Spieker, Andrew J.; Greevy, Robert A.; Nelson, Lyndsay A.; Mayberry, Lindsay S.
  作者单位：Vanderbilt University; Vanderbilt University
  摘要：Estimation of local average treatment effects in randomized trials typically relies upon the exclusion restriction assumption in cases where we are unwilling to rule out the possibility of unmeasured confounding. Under this assumption, treatment effects are mediated through the post-randomization variable being conditioned upon and directly attributable to neither the randomization itself nor its latent descendants. Recently, there has been interest in mobile health interventions to provide he...
• INFERENCE IN BAYESIAN ADDITIVE VECTOR AUTOREGRESSIVE TREE MODELS AI翻译
  作者：Huber, Florian; Rossini, Luca
  作者单位：Salzburg University; University of Milan
  摘要：Vector autoregressive (VAR) models assume linearity between the endogenous variables and their lags. This assumption might be overly restrictive and could have a deleterious impact on forecasting accuracy. As a solution we propose combining VAR with Bayesian additive regression tree (BART) models. The resulting Bayesian additive vector autoregressive tree (BAVART) model is capable of capturing arbitrary nonlinear relations between the endogenous variables and the covariates without much input ...
• ESTIMATING THE EFFECTIVENESS OF PERMANENT PRICE REDUCTIONS FOR COMPETING PRODUCTS USING MULTIVARIATE BAYESIAN STRUCTURAL TIME SERIES MODELS AI翻译
  作者：Menchetti, Fiammetta; Bojinov, Iavor
  作者单位：University of Florence; Harvard University
  摘要：The Florence branch of an Italian supermarket chain recently implemented a strategy that permanently lowered the price of numerous store brands in several product categories. To quantify the impact of such a policy change, researchers often use synthetic control methods for estimating causal effects when a subset of units receive a single persistent treatment and the rest are unaffected by the change. In our applications, however, competitor brands not assigned to treatment are likely impacted...
• MODELING NONSTATIONARY TEMPERATURE MAXIMA BASED ON EXTREMAL DEPENDENCE CHANGING WITH EVENT MAGNITUDE AI翻译
  作者：Zhong, Peng; Huser, Raphael; Opitz, Thomas
  作者单位：King Abdullah University of Science & Technology; INRAE
  摘要：The modeling of spatiotemporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate and assess the environmental, societal, economic and health-related risks they entail. Here, we study annual temperature maxima over Southern Europe using a century-spanning dataset observed at 44 monitoring stations. Extending the spectral representation of max-stable processes, our modeling framework relies on a novel construction of max-infi...
• BAYESIAN ADJUSTMENT FOR PREFERENTIAL TESTING IN ESTIMATING INFECTION FATALITY RATES, AS MOTIVATED BY THE COVID-19 PANDEMIC AI翻译
  作者：Campbell, Harlan; de Valpine, Perry; Maxwell, Lauren; de Jong, Valentijn M. T.; Debray, Thomas P. A.; Jaenisch, Thomas; Gustafson, Paul
  作者单位：University of British Columbia; University of California System; University of California Berkeley; Ruprecht Karls University Heidelberg; Utrecht University; Utrecht University Medical Center; Utrecht University; Utrecht University Medical Center; Colorado School of Public Health
  摘要：A key challenge in estimating the infection fatality rate (IFR), along with its relation with various factors of interest, is determining the total number of cases. The total number of cases is not known not only because not everyone is tested but also, more importantly, because tested individuals are not representative of the population at large. We refer to the phenomenon whereby infected individuals are more likely to be tested than noninfected individuals as preferential testing. An open q...
• PREELECTORAL POLLS VARIABILITY: A HIERARCHICAL BAYESIAN MODEL TO ASSESS THE ROLE OF HOUSE EFFECTS WITH APPLICATION TO ITALIAN ELECTIONS AI翻译
  作者：De Stefano, Domenico; Pauli, Francesco; Torelli, Nicola
  作者单位：University of Trieste; University of Trieste
  摘要：It is widely known that preelectoral polls often suffer from nonsampling errors that pollsters try to compensate for in final estimates by means of diverse ad hoc adjustments, thus leading to well-known house effects. We propose a Bayesian hierarchical model to investigate the role of house effects on the total variability of predictions. To illustrate the model, data from preelectoral polls in Italy in 2006, 2008 and 2013 are considered. Unlike alternative techniques or models, our proposal l...
• IN-GAME WIN PROBABILITIES FOR THE NATIONAL RUGBY LEAGUE AI翻译
  作者：Guan, Tianyu; Nguyen, Robert; Cao, Jiguo; Swartz, Tim
  作者单位：Brock University; University of New South Wales Sydney; Simon Fraser University
  摘要：This paper develops new methods for providing instantaneous in-game win probabilities for the National Rugby League. Besides the score differential, betting odds, and real-time features extracted from the match event data are also used as inputs to inform the in-game win probabilities. Rugby matches evolve continuously in time, and the circumstances change over the duration of the match. Therefore, the match data are considered as functional data, and the in-game win probability is a function ...
• LIKELIHOOD-BASED BACTERIAL IDENTIFICATION APPROACH FOR BIMICROBIAL MASS SPECTROMETRY DATA AI翻译
  作者：Ryu, So Young
  作者单位：Nevada System of Higher Education (NSHE); University of Nevada Reno
  摘要：Mass spectrometry is a potential diagnostic tool for rapid bacterial detection. However, in order to use this technology in clinical settings, it is important to develop sound statistical algorithms that can accurately analyze polymicrobial mass spectrometry data. Here, we propose a likelihood-based bacterial identification algorithm for bimicrobial mass spectrometry data. Specifically, we introduce a two-component mixture model with partially known labels. This method can model peaks with unk...
• ACCOUNTING FOR DROP-OUT USING INVERSE PROBABILITY CENSORING WEIGHTS IN LONGITUDINAL CLUSTERED DATA WITH INFORMATIVE CLUSTER SIZE AI翻译
  作者：Mitani, Aya A.; Kaye, Elizabeth K.; Nelson, Kerrie P.
  作者单位：University of Toronto; Boston University; Boston University
  摘要：Periodontal disease is a serious gum infection impacting half of the U.S. adult population that may lead to loss of teeth. Using standard marginal models to study the association between patient-level predictors and tooth-level outcomes can lead to biased estimates because the independence assumption between the outcome (periodontal disease) and cluster size (number of teeth per patient) is violated. Specifically, the baseline number of teeth of a patient is informative. In this setting a clus...
• BIDIMENSIONAL LINKED MATRIX FACTORIZATION FOR PAN-OMICS PAN-CANCER ANALYSIS AI翻译
  作者：Lock, Eric F.; Park, Jun Young; Hoadley, Katherine A.
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Toronto; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Several modern applications require the integration of multiple large data matrices that have shared rows and/or columns. For example, cancer studies that integrate multiple omics platforms across multiple types of cancer, pan-omics pan-cancer analysis, have extended our knowledge of molecular heterogeneity beyond what was observed in single tumor and single platform studies. However, these studies have been limited by available statistical methodology. We propose a flexible approach to the si...