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作者：Breidt, F. Jay; Opsomer, Jean D.; Sanchez-Borrego, Ismael
作者单位：Colorado State University System; Colorado State University Fort Collins
摘要：Fine stratification is commonly used to control the distribution of a sample from a finite population and to improve the precision of resulting estimators. One-per-stratum designs represent the finest possible stratification and occur in practice, but designs with very low numbers of elements per stratum (say, two orthree). are also common. The classical variance estimator in this context is the collapsed stratum estimator, which relies on creating larger pseudo-strata and computing the sum of...
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作者：Tang, Jin; Li, Yehua; Guan, Yongtao
作者单位：Iowa State University; Iowa State University
摘要：We model generalized longitudinal data from multiple treatment groups by a class of semiparametric analysis of covariance models, which take into account the parametric effects of time dependent covariates and the nonparametric time effects. In these models, the treatment effects are represented by nonparametric functions of time and we propose a generalized quasi-likelihood ratio test procedure to test if these functions are identical. Our estimation procedure is based on profile estimating e...
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作者：Conti, Pier Luigi; Marella, Daniela; Scanu, Mauro
作者单位：Sapienza University Rome; Roma Tre University
摘要：The goal of statistical matching is the estimation of a joint distribution having observed only samples from its marginals. The lack of joint observations on the variables of interest is the reason of uncertainty about the joint population distribution function. In the present article, the notion of matching error is introduced, and upper-bounded via an appropriate measure of uncertainty. Then, an estimate of the distribution function for the variables not jointly observed is constructed on th...
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作者：Li, Degui; Qian, Junhui; Su, Liangjun
作者单位：University of York - UK; Shanghai Jiao Tong University; Singapore Management University
摘要：In this article, we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furt...
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作者：Patilea, Valentin; Sanchez-Sellero, Cesar; Saumard, Matthieu
作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); Bucharest University of Economic Studies; Universidade de Santiago de Compostela; Pontificia Universidad Catolica de Valparaiso
摘要：This article examines the problem of nonparametric testing,for the no-effect of a random covariate (or predictor) on a functional response. This means testing whether the conditional expectation of the response given the covariate is almost surely zero or not, without imposing any model relating response and covariate. The covariate could be univariate, multivariate, or functional. Our test statistic is a quadratic form involving univariate nearest neighbor smoothing and the asymptotic critica...
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作者：Bura, Efstathia; Duarte, Sabrina; Forzani, Liliana
作者单位：George Washington University; National University of the Littoral
摘要：We develop methodology for identifying and estimating sufficient reductions in regressions with predictors that, given the response, follow a multivariate exponential family distribution. This setup includes regressions where predictors are all continuous, all categorical, or mixtures of categorical and continuous. We derive the minimal sufficient reduction of the predictors and its maximum likelihood estimator by modeling the conditional distribution of the predictors given the response. Wher...
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作者：Chen, Jingxiang; Liu, Yufeng; Zeng, Donglin; Song, Rui; Zhao, Yingqi; Kosorok, Michael R.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; North Carolina State University; Fred Hutchinson Cancer Center; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Xu, Muller, Wahed, and Thall proposed a Bayesian model to analyze an acute leukemia study involving multi :stage chemotherapy regimes. We discuss two alternative methods, Q-learning and O-learning, to solve the same problem from the machine learning point of view. The numerical studies show that these methods can be flexible and have advantages in some situations to handle treatment heterogeneity while being robust to model misspecification.
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作者：Yue, Chen; Zipunnikov, Vadim; Bazin, Pierre-Louis; Dzung Pham; Reich, Daniel; Crainiceanu, Ciprian; Caffo, Brian
作者单位：Johns Hopkins University; Max Planck Society; United States Department of Defense; Center for Neuroscience & Regenerative Medicine (CNRM); National Institutes of Health (NIH) - USA; National Institutes of Health (NIH) - USA; NIH National Institute of Neurological Disorders & Stroke (NINDS)
摘要：In this article, we are concerned with data generated from a diffusion tensor imaging (DTI). experiment. The goal is to parameterize manifold-like white matter tracts, such as the corpus callosum, using principal surfaces. The problem is approached by finding a geometrically motivated surface-based representation of the corpus callosum and visualized fractional anisotropy (FA) values projected onto the surface. The method also applies to any other diffusion summary. An algorithm is proposed th...
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作者：Fisher, Aaron; Caffo, Brian; Schwartz, Brian; Zipunnikov, Vadim
作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
摘要：Many have suggested a bootstrap procedure for estimating the sampling variability of principal component analysis (PCA) results. However, when the number of measurements per subject (p) is much larger than the number of subjects (n), calculating and storing the leading principal components (PCs) from each bootstrap sample can be computationally infeasible. To address this, we outline methods for fast, exact calculation of bootstrap PCs, eigenvalues, and scores. Our methods leverage the fact th...
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作者：Han, Peisong; Lawless, Jerald F.
作者单位：University of Waterloo
