Journal of the American Statistical Association

最新文章

• Spatial Statistical Data Fusion for Remote Sensing Applications AI翻译
  作者：Hai Nguyen; Cressie, Noel; Braverman, Amy
  作者单位：California Institute of Technology; National Aeronautics & Space Administration (NASA); NASA Jet Propulsion Laboratory (JPL); University System of Ohio; Ohio State University; University System of Ohio; Ohio State University
  摘要：Aerosols are tiny solid or liquid particles suspended in the atmosphere; examples of aerosols include windblown dust, sea salts, volcanic ash, smoke from wildfires, and pollution from factories. The global distribution of aerosols is a topic of great interest in climate studies since aerosols can either cool or warm the atmosphere depending on their location, type, and interaction with clouds. Aerosol concentrations are important input components of global climate models, and it is crucial to ...
• Structural Nested Cumulative Failure Time Models to Estimate the Effects of Interventions AI翻译
  作者：Picciotto, Sally; Hernan, Miguel A.; Page, John H.; Young, Jessica G.; Robins, James M.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：In the presence of time-varying confounders affected by prior treatment, standard statistical methods for failure time analysis may be biased. Methods that correctly adjust for this type of covariate include the parametric g-formula, inverse probability weighted estimation of marginal structural Cox proportional hazards models, and g-estimation of structural nested accelerated failure time models. In this article, we propose a novel method to estimate the causal effect of a time-dependent trea...
• Meta-Analysis of Rare Binary Adverse Event Data AI翻译
  作者：Bhaumik, Dulal K.; Amatya, Anup; Normand, Sharon-Lise T.; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D.
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; New Mexico State University; Harvard University; Harvard Medical School; Carnegie Mellon University; University System of Ohio; Ohio State University; Duke University; University of Chicago; University of Chicago; University of Chicago
  摘要：We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse-event data. Special attention is paid to the case of rare adverse events that are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We deriv...
• Bootstrapping for Significance of Compact Clusters in Multidimensional Datasets AI翻译
  作者：Maitra, Ranjan; Melnykov, Volodymyr; Lahiri, Soumendra N.
  作者单位：Iowa State University; Iowa State University; North Dakota State University Fargo; Texas A&M University System; Texas A&M University College Station
  摘要：This article proposes a bootstrap approach for assessing significance in the clustering of multidimensional datasets. The procedure compares two models and declares the more complicated model a better candidate if there is significant evidence in its favor. The performance of the procedure is illustrated on two well-known classification datasets and comprehensively evaluated in terms of its ability to estimate the number of components via extensive simulation studies, with excellent results. T...
• Testing for Gene-Environment and Gene-Gene Interactions Under Monotonicity Constraints AI翻译
  作者：Han, Summer S.; Rosenberg, Philip S.; Chatterjee, Nilanjan
  作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics
  摘要：Recent genome-wide association studies (GWASs) designed to detect the main effects of genetic markers have had considerable success with many findings validated by replication studies. However, relatively few findings of gene-gene or gene-environment interactions have been successfully reproduced. Besides the main issues associated with insufficient sample size in current studies, a complication is that interactions that rank high based on p-values often correspond to extreme forms of joint ef...
• Deconvolution When Classifying Noisy Data Involving Transformations AI翻译
  作者：Carroll, Raymond; Delaigle, Aurore; Hall, Peter
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Melbourne
  摘要：In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully d...
• Robust Estimation of Multivariate Location and Scatter in the Presence of Missing Data AI翻译
  作者：Danilov, Mike; Yohai, Victor J.; Zamar, Ruben H.
  作者单位：Alphabet Inc.; Google Incorporated; University of Buenos Aires; University of British Columbia
  摘要：Two main issues regarding data quality are data contamination (outliers) and data completion (missing data). These two problems have attracted much attention and research but surprisingly, they are seldom considered together. Popular robust methods such as S-estimators of multivariate location and scatter offer protection against outliers but cannot deal with missing data, except for the obviously inefficient approach of deleting all incomplete cases. We generalize the definition of S-estimato...
• Spatio-Spectral Mixed-Effects Model for Functional Magnetic Resonance Imaging Data AI翻译
  作者：Kang, Hakmook; Ombao, Hernando; Linkletter, Crystal; Long, Nicole; Badre, David
  作者单位：Vanderbilt University; University of California System; University of California Irvine; Brown University; Brown University
  摘要：The goal of this article is to model cognitive control related activation among predefined regions of interest (ROIs) of the human brain while properly adjusting for the underlying spatio-temporal correlations. Standard approaches to fMRI analysis do not simultaneously take into account both the spatial and temporal correlations that are prevalent in fMRI data. This is primarily due to the computational complexity of estimating the spatio-temporal covariance matrix. More specifically, they do ...
• Multiple Testing of Composite Null Hypotheses in Heteroscedastic Models AI翻译
  作者：Sun, Wenguang; McLain, Alexander C.
  作者单位：University of Southern California; National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
  摘要：In large-scale studies, the true effect sizes often range continuously from zero to small to large, and are observed with heteroscedastic errors. In practical situations where the failure to reject small deviations from the null is inconsequential, specifying an indifference region (or forming composite null hypotheses) can greatly reduce the number of unimportant discoveries in multiple testing. The heteroscedasticity issue poses new challenges for multiple testing with composite nulls. In pa...
• Using Mixed Integer Programming for Matching in an Observational Study of Kidney Failure After Surgery AI翻译
  作者：Zubizarreta, Jose R.
  作者单位：University of Pennsylvania
  摘要：This article presents a new method for optimal matching in observational studies based on mixed integer programming. Unlike widely used matching methods based on network algorithms, which attempt to achieve covariate balance by minimizing the total sum of distances between treated units and matched controls, this new method achieves covariate balance directly, either by minimizing both the total sum of distances and a weighted sum of specific measures of covariate imbalance, or by minimizing t...