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作者：Gomes, M. L.; Pestana, D.
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作者：Liu, Xuefeng; Daniels, Michael J.; Marcus, Bess
作者单位：East Tennessee State University; State University System of Florida; University of Florida; Brown University
摘要：Joint models for the association of a logitudinal binary and a longitudinal continuous process are proposed for situations in which their association is of direct interest. The models are parametrized such that the dependence between the two processes is characterized by unconstrained regression coefficients. Bayesian variable selection techniques are used to parsimoniously model these coefficients. A Markov chain Monte Carlo (MCMC) sampling algorithm is developed for sampling from the posteri...
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作者：Sun, Liuquan; Zhang, Zhigang
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Memorial Sloan Kettering Cancer Center
摘要：The mean residual life function is an attractive alternative to the survival function or the hazard function of a survival time in practice. It provides the remaining life expectancy of a subject surviving Lip to time t. In this study. We propose a class of transformed mean residual life models for fitting survival data under right censoring. To estimate the model parameters. we make use of the inverse probability of censoring weighting approach and develop a system of estimating equations. Ef...
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作者：Cook, R. Dennis; Forzani, Liliana
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); National University of the Littoral
摘要：We obtain the maximum likelihood estimator of the central subspace under conditional normality of the predictors given the response. Analytically and in simulations we found that our new estimator can preform much better than sliced inverse regression, sliced average variance estimation and directional regression, and that it seems quite robust to deviations from normality.
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作者：Craiu, Radu V.; Rosenthal, Jeffrey; Yang, Chao
作者单位：University of Toronto
摘要：Starting with the seminal paper of Haario, Saksman, and Tamminen (Haario, Saksman, and Tamminen 2001), a substantial amount of work has been done to validate adaptive Markov chain Monte Carlo algorithms. In this paper we focus on two practical aspects of adaptive Metropolis samplers. First, we draw attention to the deficient performance of standard adaptation when the target distribution is multimodal. We propose a parallel chain adaptation strategy that incorporates multiple Markov chains whi...
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作者：Guan, Yongtao
作者单位：Yale University
摘要：We introduce new variance estimation procedures for second-order statistics that are computed from a single realization of intensity reweighted stationary spatial point processes. The statistics are defined either on a subset B of the observation window or on the whole window. For the former, we use subblocks that have the same size and shape as B as replicates of B in order to estimate the target variance. For the latter, we develop a subsampling estimator for a key component in the target va...
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作者：Scharpf, Robert B.; Tjelmeland, Hakon; Parmigiani, Giovanni; Nobel, Andrew B.
作者单位：Norwegian University of Science & Technology (NTNU); Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins Medicine; University of North Carolina; University of North Carolina Chapel Hill
摘要：In this article we define a hierarchical Bayesian model for microarray expression data collected from several studies and use it to identify genes that show differential expression between two conditions. Key features include shrinkage across both gene.; and studies, and flexible modeling that allows for interactions between platforms and the estimated effect, as well as concordant and discordant differential expression across studies. We evaluate the performance of our model in a comprehensiv...
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作者：Peng, Jie; Wang, Pei; Zhou, Nengfeng; Zhu, Ji
作者单位：University of California System; University of California Davis; Fred Hutchinson Cancer Center; University of Michigan System; University of Michigan
摘要：In this article, we propose a computationally efficient approach-space (Sparse PArtial Correlation Estimation)-for selecting nonzero partial correlations under the high-dimension-low-sample-size setting. This method assumes the overall sparsity of the partial correlation matrix and employs sparse regression techniques for model fitting. We illustrate the performance of space by extensive simulation studies. It is shown that space performs well in both nonzero partial correlation selection and ...
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作者：Liu, Yi; Hsu, Jason
作者单位：University System of Ohio; Ohio State University
摘要：Testing for efficacy in multiple endpoints has emerged as an important statistical problem. The Food and Drug Administration (FDA) will issue a guidance on Multiple Endpoints in the near future. When there are primary and secondary endpoints, efficacy in the secondary endpoint is relevant only if efficacy in the primary endpoint has been shown. Thus, there are defined paths to decision making. Current approaches to this problem are based on closed testing, testing all possible intersection hyp...
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作者：Cheng, Yu-Jen; Crainiceanu, Ciprian M.
作者单位：Johns Hopkins University
摘要：We propose, develop, and implement a fully Bayesian inferential approach for the Cox model when the log hazard function contains unknown smooth functions of the variables measured with error. Our approach is to model nonparametrically both the log-baseline hazard and the smooth components of the log-hazard functions using low-rank penalized splines. Careful implementation of the Bayesian inferential machinery is shown to produce remarkably better results than the naive approach. Our methodolog...
