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作者：Zhao, Jiwei; Ma, Yanyuan
作者单位：State University of New York (SUNY) System; University at Buffalo, SUNY; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Tang et al. (2003) considered a regression model with missing response, where the missingness mechanism depends on the value of the response variable and hence is nonignorable. They proposed three pseudolikelihood estimators, based on different treatments of the probability distribution of the completely observed covariates. The first assumes the distribution of the covariate to be known, the second estimates this distribution parametrically, and the third estimates the distribution nonparamet...
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作者：Mao, Lu
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：We introduce a general class of causal estimands which extends the familiar notion of average treatment effect. The class is defined by a contrast function, prespecified to quantify the relative favourability of one outcome over another, averaged over the marginal distributions of two potential outcomes. Natural estimators arise in the form of U-statistics. We derive both a naive inverse propensity score weighted estimator and a class of locally efficient and doubly robust estimators. The usef...
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作者：Blasques, F.; Koopman, S. J.; Lucas, A.
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作者：Zhou, Quan; Ernst, Philip A.; Morgan, Kari Lock; Rubin, Donald B.; Zhang, Anru
作者单位：Rice University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Harvard University; University of Wisconsin System; University of Wisconsin Madison
摘要：The seminal work of Morgan & Rubin (2012) considers rerandomization for all the units at one time. In practice, however, experimenters may have to rerandomize units sequentially. For example, a clinician studying a rare disease may be unable to wait to perform an experiment until all the experimental units are recruited. Our work offers a mathematical framework for sequential rerandomization designs, where the experimental units are enrolled in groups. We formulate an adaptive rerandomization ...
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作者：Massam, H.; Li, Q.; Gao, X.
作者单位：York University - Canada; Sun Yat Sen University
摘要：Graphical Gaussian models with edge and vertex symmetries were introduced by Hojsgaard & Lauritzen (2008), who gave an algorithm for computing the maximum likelihood estimate of the precision matrix for such models. In this paper, we take a Bayesian approach to its estimation. We consider only models with symmetry constraints and which thus form a natural exponential family with the precision matrix as the canonical parameter. We identify the Diaconis-Ylvisaker conjugate prior for these models...
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作者：Chung, Yunro; Ivanova, Anastasia; Hudgens, Michael G.; Fine, Jason P.
作者单位：Fred Hutchinson Cancer Center; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：We consider the estimation of the semiparametric proportional hazards model with an unspecified baseline hazard function where the effect of a continuous covariate is assumed to be monotone. Previous work on nonparametric maximum likelihood estimation for isotonic proportional hazard regression with right-censored data is computationally intensive, lacks theoretical justification, and may be prohibitive in large samples. In this paper, partial likelihood estimation is studied. An iterative qua...
