The Annals of Applied Statistics

最新文章

• ASSESSING TREATMENT EFFECT THROUGH COMPLIANCE SCORE IN RANDOMIZED TRIALS WITH NONCOMPLIANCE AI翻译
  作者：Hu, Zonghui; Zhang, Zhiwei; Follmann, Dean
  作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
  摘要：A randomized trial is the gold standard for assessing the benefit of a treat-ment versus a control. When noncompliance is present, treatment effect de-pends on the tendency to comply-an attribute that is not directly measurable. Though the principal causal effect has been the most important for handling noncompliance, it is not immediately applicable to clinical decision-making as it targets the average effect in the latent strata of potential compliance. In this work, we propose the concept o...
• CO-CLUSTERING OF MULTIVARIATE FUNCTIONAL DATA FOR THE ANALYSIS OF AIR POLLUTION IN THE SOUTH OF FRANCE AI翻译
  作者：Bouveyron, Charles; Jacques, Julien; Schmutz, Amandine; Simoes, Fanny; Bottini, Silvia
  作者单位：Universite Cote d'Azur; Inria; Centre National de la Recherche Scientifique (CNRS); Universite Cote d'Azur
  摘要：Nowadays, air pollution is a major threat for public health with clear relationships with many diseases, especially cardiovascular ones. The spatiotemporal study of pollution is of great interest for governments and local authorities when deciding for public alerts or new city policies against pollution increase. The aim of this work is to study spatiotemporal profiles of environmental data collected in the south of France (Region Sud) by the public agency AtmoSud. The idea is to better unders...
• CONTRASTIVE LATENT VARIABLE MODELING WITH APPLICATION TO CASE-CONTROL SEQUENCING EXPERIMENTS AI翻译
  作者：Jones, Andrew; Townes, F. William; Li, Didong; Engelhardt, Barbara E.
  作者单位：Princeton University
  摘要：High-throughput RNA-sequencing (RNA-seq) technologies are powerful tools for understanding cellular state. Often, it is of interest to quantify and to summarize changes in cell state that occur between experimental or biological conditions. Differential expression is typically assessed using univariate tests to measure genewise shifts in expression. However, these methods largely ignore changes in transcriptional correlation. Furthermore, there is a need to identify the low-dimensional structu...
• 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 DATA SYNTHESIS AND THE UTILITY-RISK TRADE-OFF FOR MIXED EPIDEMIOLOGICAL DATA AI翻译
  作者：Feldman, Joseph; Kowal, Daniel R.
  作者单位：Rice University
  摘要：Much of the microdata used for epidemiological studies contain sensi-tive measurements on real individuals. As a result, such microdata cannot be published out of privacy concerns, and without public access to these data, any statistical analyses originally published on them are nearly impos-sible to reproduce. To promote the dissemination of key datasets for analy-sis without jeopardizing the privacy of individuals, we introduce a cohesive Bayesian framework for the generation of fully synthe...
• DATA-ADAPTIVE EFFICIENT ESTIMATION STRATEGIES FOR BIOMARKER STUDIES EMBEDDED IN RANDOMIZED TRIALS AI翻译
  作者：Zhang, Weiz; Zhang, Zhi wei; Troendle, James F.; Liu, Aiyi
  作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI); National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
  摘要：Predictive and prognostic biomarkers are increasingly important in clini-cal research and practice. Biomarker studies are frequently embedded in ran-domized clinical trials with biospecimens collected at baseline and assayed for biomarkers, either in real time or retrospectively. This article proposes efficient estimation strategies for two study settings in terms of biomarker ascertainment: a complete-data setting in which the biomarker is measured for all subjects in the trial, and a two-pha...
• MODEL CALIBRATION USING SEMICONTINUOUS SPATIAL DATA AI翻译
  作者：Chang, Won; Konomi, Bledar A.; Karagiannis, Georgios; Guan, Yawen; Haran, Murali
  作者单位：University System of Ohio; University of Cincinnati; Durham University; University of Nebraska System; University of Nebraska Lincoln; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Rapid changes in Earth's cryosphere caused by human activity can lead to significant environmental impacts. Computer models provide a useful tool for understanding the behavior and projecting the future of Arctic and Antarctic ice sheets. However, these models are typically subject to large parametric uncertainties, due to poorly constrained model input parameters that govern the behavior of simulated ice sheets. Computer model calibration provides a formal statistical framework to infer param...
• DETECTION OF TWO-WAY OUTLIERS IN MULTIVARIATE DATA AND APPLICATION TO CHEATING DETECTION IN EDUCATIONAL TESTS AI翻译
  作者：Chen, Yunxiao; Lu, Yan; Moustaki, Irini
  作者单位：University of London; London School Economics & Political Science
  摘要：The paper proposes a new latent variable model for the simultaneous (two-way) detection of outlying individuals and items for item-response-type data. The proposed model is a synergy between a factor model for binary responses and continuous response times that captures normal item response behaviour and a latent class model that captures the outlying individuals and items. A statistical decision framework is developed under the proposed model that provides compound decision rules for controll...
• INTEGRATED QUANTILE RANK TEST (IQRAT) FOR GENE-LEVEL ASSOCIATIONSINTEGRATED QUANTILE RANK TEST (IQRAT) FOR GENE-LEVEL ASSOCIATIONS AI翻译
  作者：Wang, Tianying; Ionita-Laza, Iuliana; Wei, Ying
  作者单位：Tsinghua University; Tsinghua University; Columbia University
  摘要：Gene-based testing is a commonly employed strategy in many genetic association studies. Gene-trait associations can be complex due to underlying population heterogeneity, gene-environment interactions, and various other reasons. Existing gene-based tests, such as burden and sequence kernel association tests (SKAT), are mean-based tests and may miss or underestimate higher-order associations that could be scientifically interesting. In this paper we propose a new family of gene-level associatio...