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作者：Zhang, Han; Deng, Lu; Schiffman, Mark; Qin, Jing; Yu, Kai
作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：Meta-analysis has become a powerful tool for improving inference by gathering evidence from multiple sources. It pools summary-level data from different studies to improve estimation efficiency with the assumption that all participating studies are analysed under the same statistical model. It is challenging to integrate external summary data calculated from different models with a newly conducted internal study in which individual-level data are collected. We develop a novel statistical infer...
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作者：Jin, Shaobo; Andersson, Bjorn
作者单位：Uppsala University; University of Oslo
摘要：Numerical quadrature methods are needed for many models in order to approximate integrals in the likelihood function. In this note, we correct the error rate given by Liu & Pierce (1994) for integrals approximated with adaptive Gauss-Hermite quadrature and show that the approximation is less accurate than previously thought. We discuss the relationship between the error rates of adaptive Gauss-Hermite quadrature and Laplace approximation, and provide a theoretical explanation of simulation res...
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作者：Al Mohamad, Diaa; Van Zwet, Erik W.; Cator, Eric; Goeman, Jelle J.
作者单位：Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC; Radboud University Nijmegen
摘要：We present a new general method for constrained likelihood ratio testing which, when few constraints are violated, improves upon the existing approach in the literature that compares the likelihood ratio with the quantile of a mixture of chi-squared distributions; the improvement is in terms of both simplicity and power. The proposed method compares the constrained likelihood ratio statistic against the quantile of only one chi-squared random variable with data-dependent degrees of freedom. Th...
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作者：Kedagni, Desire; Mourifie, Ismael
作者单位：Iowa State University; University of Toronto
摘要：This paper proposes a new set of testable implications for the instrumental variable independence assumption for discrete treatment, but unrestricted outcome and instruments: generalized instrumental inequalities. When outcome and treatment are both binary, but instruments are unrestricted, we show that the generalized instrumental inequalities are necessary and sufficient to detect all observable violations of the instrumental variable independence assumption. To test the generalized instrume...
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作者：Roverato, Alberto; Castelo, Robert
作者单位：University of Padua; Pompeu Fabra University
摘要：A graphical model provides a compact and efficient representation of the association structure in a multivariate distribution by means of a graph. Relevant features of the distribution are represented by vertices, edges and higher-order graphical structures such as cliques or paths. Typically, paths play a central role in these models because they determine the dependence relationships between variables. However, while a theory of path coefficients is available for directed graph models, littl...
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作者：Heng, J.; Jacob, P. E.
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作者：Bachoc, Francois; Genton, Marc G.; Nordhausen, Klaus; Ruiz-Gazen, Anne; Virta, Joni
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; King Abdullah University of Science & Technology; Technische Universitat Wien; Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; University of Turku
摘要：Recently a blind source separation modelwas suggested for spatial data, along with an estimator based on the simultaneous diagonalization of two scatter matrices. The asymptotic properties of this estimator are derived here, and a new estimator based on the joint diagonalization of more than two scatter matrices is proposed. The asymptotic properties and merits of the novel estimator are verified in simulation studies. A real-data example illustrates application of the method.
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作者：Yoon, Grace; Carroll, Raymond J.; Gaynanova, Irina
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：Canonical correlation analysis investigates linear relationships between two sets of variables, but it often works poorly on modern datasets because of high dimensionality and mixed data types such as continuous, binary and zero-inflated. To overcome these challenges, we propose a semiparametric approach to sparse canonical correlation analysis based on the Gaussian copula. The main result of this paper is a truncated latent Gaussian copula model for data with excess zeros, which allows us to ...
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作者：Zhou, Ruixuan Rachel; Wang, Liewei; Zhao, Sihai Dave
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; Mayo Clinic
摘要：Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in the presence of high-dimensional mediators for linear mediation models. We develop methods for both incomplete mediation, where a direct effect may exist, and complete mediation, where the direct effect is known to be absent. We prove consistency and asymptotic normality of our indirect effect estimators. Under compl...
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作者：Ning, Yang; Sida, Peng; Imai, Kosuke
作者单位：Cornell University; Microsoft; Harvard University
摘要：We propose a robust method to estimate the average treatment effects in observational studies when the number of potential confounders is possibly much greater than the sample size. Our method consists of three steps. We first use a class of penalized M-estimators for the propensity score and outcome models. We then calibrate the initial estimate of the propensity score by balancing a carefully selected subset of covariates that are predictive of the outcome. Finally, the estimated propensity ...
