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作者：Cox, D. R.
作者单位：University of Oxford
摘要：A relationship due to W. G. Cochran showing the effect on least squares regression coefficients of marginalizing over or conditioning on an explanatory variable is generalized to quantile regression coefficients. The condition under which conditioning does not induce interaction or effect reversal is shown. Examples are given. The discussion is simplest when all variables are continuous; the extension to discrete variables is outlined.
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作者：Ando, Tomohiro
作者单位：Keio University
摘要：The problem of evaluating the goodness of the predictive distributions of hierarchical Bayesian and empirical Bayes models is investigated. A Bayesian predictive information criterion is proposed as an estimator of the posterior mean of the expected loglikelihood of the predictive distribution when the specified family of probability distributions does not contain the true distribution. The proposed criterion is developed by correcting the asymptotic bias of the posterior mean of the loglikeli...
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作者：Wang, Yuanjia; Clark, Lorraine N.; Marder, Karen; Rabinowitz, Daniel
作者单位：Columbia University; Columbia University; Columbia University; Columbia University
摘要：We present a nonparametric estimator of genotype-specific age-at-onset distributions from kin-cohort data. Standard error calculations. are derived and the methodology is illustrated through an analysis of the influence of mutations of the Parkin gene on Parkinson's disease. Semiparametric efficiency considerations are briefly discussed.
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作者：Chen, Y. Q.; Yang, J.; Cheng, S.; Jackson, J. B.
作者单位：Fred Hutchinson Cancer Center; University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California San Francisco; Johns Hopkins University
摘要：To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are th...
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作者：Rosen, Ori; Stoffer, David S.
作者单位：University of Texas System; University of Texas El Paso; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：The classical method for estimating the spectral density of a multivariate time series is first to calculate the periodogram, and then to smooth it to obtain a consistent estimator. Typically, to ensure the estimate is positive definite, all the elements of the periodogram. are smoothed the same way. There are, however, many situations for which different components of the spectral matrix have different degrees of smoothness. We propose a Bayesian approach that uses Markov chain Monte Carlo te...
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作者：Oller, Ramon; Gomez, Guadalupe; Calle, M. Luz
作者单位：Universitat de Vic - Universitat Central de Catalunya (UVic-UCC); Universitat de Vic - Universitat Central de Catalunya (UVic-UCC)
摘要：The constant-sum property given in Oller et al. (2004) for censoring models justifies the use of a simplified likelihood to obtain the nonparametric maximum likelihood estimator of the lifetime distribution. In this paper we study the relevance of the constant-sum property in the identifiability of the lifetime distribution. We show that the lifetime distribution is not identifiable outside the class of constant-sum models. We also show that the lifetime probabilities assigned to the observabl...
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作者：Huang, Yifan; Hsu, Jason C.
作者单位：State University System of Florida; University of South Florida; University System of Ohio; Ohio State University
摘要：Holm's method and Hochberg's method for multiple testing can be viewed as step-down and step-up versions of the Bonferroni test. We show that both are special cases of partition testing. The difference is that, while Holm's method tests each partition hypothesis using the largest order statistic, setting a critical value based on the Bonferroni inequality, Hochberg's method tests each partition hypothesis using all the order statistics, setting a series of critical values based on Simes' inequ...
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作者：Lin, Wei; Kulasekera, K. B.
作者单位：University System of Ohio; Ohio University; Clemson University
摘要：We provide a proof for the identifiability for both single-index models and partially linear single-index models assuming only the continuity of the regression function, a condition much weaker than the differentiability conditions assumed in the existing literature. Our discussion is then extended to the identifiability of the additive-index models.
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作者：Jasra, Ajay; Stephens, David A.; Holmes, Christopher C.
作者单位：Imperial College London; McGill University; University of Oxford
摘要：We present an extension of population-based Markov chain Monte Carlo to the transdimensional case. A major challenge is that of simulating from high- and transdimensional target measures. In such cases, Markov chain Monte Carlo methods may not adequately traverse the support of the target; the simulation results will be unreliable. We develop population methods to deal with such problems, and give a result proving the uniform ergodicity of these population algorithms, under mild assumptions. T...
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作者：Vansteelandt, Stijn; Rotnitzky, Andrea; Robins, James
作者单位：Ghent University; Universidad Torcuato Di Tella; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We propose a new class of models for making inference about the mean of a vector of repeated outcomes when the outcome vector is incompletely observed in some study units and missingness is nonmonotone. Each model in our class is indexed by a set of unidentified selection-bias functions which quantify the residual association of the outcome at each occasion t and the probability that this outcome is missing after adjusting for variables observed prior to time t and for the past nonresponse pat...
