Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods throughout all disciplines that make use of data, including economic, social, biological, physical, engineering, and health sciences and the humanities.
作者：Lee, Giwhyun; Ding, Yu; Genton, Marc G.; Xie, Le
作者单位：Texas A&M University System; Texas A&M University College Station; King Abdullah University of Science & Technology; Texas A&M University System; Texas A&M University College Station
摘要：In the wind industry, a power curve refers to the functional relationship between the power output generated by a wind turbine and the wind speed at the time of power generation. Power curves are used in practice for a number of important tasks including predicting wind power production and assessing a turbine's energy production efficiency. Nevertheless, actual wind power data indicate that the power output is affected by more than just wind speed. Several other environmental factors, such as...
作者单位：Centers for Disease Control & Prevention - USA; CDC National Center for Health Statistics (NCHS)
摘要：The International Year of Statistics, 2013, focused on outreach in a wonderful way. As we celebrate the ASA's 175th anniversary in 2014, it is worthwhile to look inward as well and think about how to keep our association and profession strong, so that our successors will be able to celebrate the 275th anniversary. The ASA, with its long history, its fine staff and organization, and its financial resource base, is well positioned to serve the profession, and indeed society, and it is very succe...
作者：Fienberg, Stephen E.; Hodges, James S.; Luo, Liying
作者单位：Carnegie Mellon University; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
作者单位：Fudan University; University of Michigan System; University of Michigan
摘要：In this article, we propose a statistical model for the purpose of identifying a subgroup that has an enhanced treatment effect as well as the variables that are predictive of the subgroup membership. The need for such subgroup identification arises in clinical trials and in market segmentation analysis. By using a structured logistic-normal mixture model, our proposed framework enables us to perform a confirmatory statistical test for the existence of subgroups, and at the same time, to const...
作者单位：State University System of Florida; University of Florida; University of Texas System; University of Texas Austin
摘要：We develop a Bayesian nonparametric model for a longitudinal response in the presence of nonignorable missing data. Our general approach is to first specify a working model that flexibly models the missingness and full outcome processes jointly. We specify a Dirichlet process mixture of missing at random (MAR) models as a prior on the joint distribution of the working model. This aspect of the model governs the fit of the observed data by modeling the observed data distribution as the marginal...
摘要：An observational study draws inferences about treatment effects when treatments are not randomly assigned, as they would be in a randomized experiment. The naive analysis of an observational study assumes that adjustments for measured covariates suffice to remove bias from nonrandom treatment assignment. A sensitivity analysis in an observational study determines the magnitude of bias from nonrandom treatment assignment that would need to be present to alter the qualitative conclusions of the ...
作者单位：University of Texas System; UTMD Anderson Cancer Center; University of Texas System; University of Texas Health Science Center Houston; University of Texas School Public Health; George Washington University
摘要：Response-adaptive designs have recently attracted more and more attention in the literature because of its advantages in efficiency and medical ethics. To develop personalized medicine, covariate information plays an important role in both design and analysis of clinical trials. A challenge is how to incorporate covariate information in response-adaptive designs while considering issues of both efficiency and medical ethics. To address this problem, we propose a new and unified family of covar...
作者：Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：The aim of this article is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issu...
作者：Scealy, J. L.; de Caritat, Patrice; Grunsky, Eric C.; Tsagris, Michail T.; Welsh, A. H.
作者单位：Australian National University; Geoscience Australia; Australian National University; Natural Resources Canada; Lands & Minerals Sector - Natural Resources Canada; Geological Survey of Canada; Australian National University
摘要：Geochemical surveys collect sediment or rock samples, measure the concentration of chemical elements, and report these typically either in weight percent or in parts per million (ppm). There are usually a large number of elements measured and the distributions are often skewed, containing many potential outliers. We present a new robust principal component analysis (PCA) method for geochemical survey data, that involves first transforming the compositional data onto a manifold using a relative...
作者单位：Universite Libre de Bruxelles; Princeton University
摘要：Independent component analysis (ICA) recently has attracted much attention in the statistical literature as an appealing alternative to elliptical models. Whereas k-dimensional elliptical densities depend on one single unspecified radial density, however, k-dimensional independent component distributions involve k unspecified component densities. In practice, for given sample size n and dimension k, this makes the statistical analysis much harder. We focus here on the estimation, from an indep...
