The Annals of Applied Statistics

最新文章

• AVERAGING POLYHAZARD MODELS USING PIECEWISE DETERMINISTIC MONTE CARLO WITH APPLICATIONS TO DATA WITH LONG-TERM SURVIVORS AI翻译
  作者：Ardcastle, Uke; Ivingstone, Amuel; Aio, Ianluca
  作者单位：University of London; University College London
  摘要：Polyhazard models are a class of flexible parametric models for modelling survival over extended time horizons. Their additive hazard structure allows for flexible, nonproportional hazards whose characteristics can change over time while retaining a parametric form, which allows for survival to be extrapolated beyond the observation period of a study. Significant user input is required, however, in selecting the number of latent hazards to model, their distributions and the choice of which var...
• MODIFIED TREATMENT POLICY EFFECT ESTIMATION WITH WEIGHTED ENERGY DISTANCE AI翻译
  作者：Jiang, Ziren; Huling, Jared D.
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：The causal effects of continuous treatments are often characterized through the average dose response function, which is challenging to estimate from observational data due to confounding and positivity violations. Modified treatment policies (MTPs) are an alternative approach that aim to assess the effect of a modification to observed treatment values and work under relaxed assumptions. Estimators for MTPs generally focus on estimating the conditional density of treatment, given covariates, a...
• DYNAMIC PREDICTION WITH PENALIZED JOINT FRAILTY MODEL OF HIGH-DIMENSIONAL RECURRENT EVENT DATA AND A SURVIVAL OUTCOME AI翻译
  作者：Sun, Jiehuan
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
  摘要：High-dimensional recurrent event data have become increasingly popular these days. For example, many of the data captured in electronic health records (EHR) may be viewed as recurrent event data. In addition, a survival outcome is the primary outcome of interest in many studies. It is of great interest to study the associations between recurrent events and the survival outcome as well as to build dynamic prediction models. Joint frailty models are commonly used to study the associations betwee...
• NONPARAMETRIC ADDITIVE VALUE FUNCTIONS: INTERPRETABLE REINFORCEMENT LEARNING WITH AN APPLICATION TO SURGICAL RECOVERY AI翻译
  作者：Medom-Nnamdi, Patrick; Smith, Timothy R.; Onnela, Jukka-Pekka; Lu, Junwei
  作者单位：Harvard University; Harvard University; Harvard Medical School; Harvard University Medical Affiliates; Brigham & Women's Hospital
  摘要：We propose a nonparametric additive model for estimating interpretable value functions in reinforcement learning, with an application in optimizing postoperative recovery through personalized, adaptive recommendations. While reinforcement learning has achieved significant success in various domains, recent methods often rely on black-box approaches, such as neural networks, which hinder the examination of individual feature contributions to a decision-making policy. Our novel method offers a f...
• ULTRA-SPARSE SMALL AREA ESTIMATION WITH SUPER HEAVY-TAILED PRIORS FOR INTERNAL MIGRATION FLOWS AI翻译
  作者：Fuquene-Patino, Jairo; Betancourt, Brenda
  作者单位：University of California System; University of California Davis; University of Chicago
  摘要：Migration flows represent an important component of global sustainable development and demographic trends. However, the dynamic nature of the migration phenomenon, known issues of undercoverage of administrative records and long intercensal periods make estimation of internal migration a very challenging task. In this work we focus on the estimation of internal migration in Colombia, which is the subject of an ongoing armed conflict that has triggered forced and voluntary population movements ...
• STATISTICAL INFERENCE FOR REGRESSION WITH IMPUTED BINARY COVARIATES WITH APPLICATION TO EMOTION RECOGNITION AI翻译
  作者：Lin, Ziqian; Huang, Danyang; Xiong, Ziyu; Wang, Hansheng
  作者单位：Peking University; Renmin University of China; Renmin University of China
  摘要：In the flourishing live streaming industry, accurate recognition of streamers' emotions has become a critical research focus with profound implications for audience engagement and content optimization. However, precise emotion coding typically requires manual annotation by trained experts, making it extremely expensive and time-consuming to obtain complete observational data for large-scale studies. Motivated by this challenge in streamer emotion recognition, we develop here a novel imputation...
• POD-BIN: A PROBABILITY OF DECISION BAYESIAN INTERVAL DESIGN FOR TIME-TO-EVENT DOSE-FINDING TRIALS WITH MULTIPLE TOXICITY GRADES AI翻译
  作者：Liu, Meizi; Lin, Ji; Mi, Gu; Lorenzato, Christelle; Chen, Xun; Ji, Yuan
  作者单位：Sanofi-Aventis; Sanofi USA; University of Chicago
  摘要：We introduce a Bayesian framework centered on the probability of decision for designing dose-finding trials. The proposed PoD-BIN design evaluates the posterior predictive probabilities of up-and-down decisions. In PoDBIN, multiple grades of toxicity, categorized as mild toxicity (MT) and doselimiting toxicity (DLT), are simultaneously modeled, with the primary outcome being time-to-toxicity for both MT and DLT. This approach allows the enrollment of new patients while previously enrolled pati...
• MORE POWER TO YOU: USING MACHINE LEARNING TO AUGMENT HUMAN CODING FOR MORE EFFICIENT INFERENCE IN TEXT-BASED RANDOMIZED TRIALS AI翻译
  作者：Mozer, Reagan; Miratrix, Luke
  作者单位：Bentley University; Harvard University
  摘要：For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to measure only a small set of dimensions across a subsample of available texts. In this work we present an inferential framework that can be used to inc...
• PERIODOGRAM REGRESSION: A TWO-STAGE MIXED EFFECTS APPROACH FOR MODELLING MULTIPLE INTEGER-VALUED TIME SERIES OF TROPICAL CYCLONE FREQUENCY AI翻译
  作者：Zhang, Lyuyuan; Qian, Guoqi; Das, Sourav
  作者单位：University of Melbourne; James Cook University
  摘要：Tropical cyclones (TC) are significant indicators of evolving climate dynamics. Two primary responses of interest are the cyclone frequency and intensity. In this paper we propose a novel integrated modelling framework for simultaneous modelling of TC frequency across several meteorological regions within Australasia. The key methodological insight is to model the second-order properties of multiple integer-valued time series in frequency domain, instead of parametric time domain models. We ta...
• GMI: GROUP-LEVEL MAIN EFFECTS AND INTERACTIONS IN HIGH-DIMENSIONAL DATA WITH APPLICATIONS TO PATHWAY AND INTERACTION DISCOVERY IN GENE EXPRESSION ANALYSIS AI翻译
  作者：Nie, Jinyu; Liu, Li; Hu, Taobo; Liu, Wei; Lin, Huazhen
  作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China; Wuhan University; Stockholm University; Sichuan University
  摘要：Genetic interactions are essential for understanding the risk and progression of complex diseases. However, signals from individual genes and their pairwise interactions are often weak; most phenotypes are driven by alterations in a limited number of pathways and interactions between them. Identifying such pathways and their interactions is critical in biomedical research. Although traditional analyses have extended beyond main effects to include gene-gene interactions, most existing methods r...