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作者：Wang, S.; Nan, B.; Zhu, N.; Zhu, J.
作者单位：University of Michigan System; University of Michigan
摘要：In many biological and other scientific applications, predictors are often naturally grouped. For example, in biological applications, assayed genes or proteins are grouped by biological roles or biological pathways. When studying the dependence of survival outcome on these grouped predictors, it is desirable to select variables at both the group level and the within-group level. In this article, we develop a new method to address the group variable selection problem in the Cox proportional ha...
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作者：Huang, Ying; Pepe, Margaret Sullivan
作者单位：Fred Hutchinson Cancer Center
摘要：The performance of a well-calibrated risk model for a binary disease outcome can be characterized by the population distribution of risk and displayed with the predictiveness curve. Better performance is characterized by a wider distribution of risk, since this corresponds to better risk stratification in the sense that more subjects are identified at low and high risk for the disease outcome. Although methods have been developed to estimate predictiveness curves from cohort studies, most stud...
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作者：Beaumont, Mark A.; Cornuet, Jean-Marie; Marin, Jean-Michel; Robert, Christian P.
作者单位：University of Reading; Imperial College London; Universite de Montpellier; Universite PSL; Universite Paris-Dauphine
摘要：Sequential techniques can enhance the efficiency of the approximate Bayesian computation algorithm, as in Sisson et al.'s (2007) partial rejection control version. While this method is based upon the theoretical works of Del Moral et al. (2006), the application to approximate Bayesian computation results in a bias in the approximation to the posterior. An alternative version based on genuine importance sampling arguments bypasses this difficulty, in connection with the population Monte Carlo m...
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作者：Mandel, M.; Fluss, R.
作者单位：Hebrew University of Jerusalem; Ministry of Health - Israel
摘要：Cross-sectional sampling is an attractive design that saves resources but results in biased data. For proper inference, one should first discover the bias function and then weigh observations appropriately. We consider cross-sectioning of the illness-death model with the aim of estimating the probability of visiting the illness state before death. We develop simple consistent and asymptotically normal estimators under various assumptions on the model and data collection and, in particular, com...
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作者：Ueki, Masao
作者单位：Yamagata University
摘要：This paper develops smooth-threshold estimating equations that can automatically eliminate irrelevant parameters by setting them as zero. The resulting estimator enjoys the oracle property in the sense of Fan & Li (2001), even in estimators for which the covariance assumption of Wang & Leng (2007) is violated, such as the Buckley-James estimator. Furthermore, the estimator can be obtained without solving a convex optimization problem. A bic-type criterion for tuning parameter selection is also...
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作者：Hardouin, Cecile; Yao, Jian-Feng
作者单位：heSam Universite; Universite Pantheon-Sorbonne; Universite de Rennes
摘要：Motivated by the modelling of non-Gaussian data or positively correlated data on a lattice, extensions of Besag's automodels to exponential families with multi-dimensional parameters have been proposed recently. We provide a multiple-parameter analogue of Besag's one-dimensional result that gives the necessary form of the exponential families for the Markov random field's conditional distributions. We propose estimation of parameters by maximum pseudolikelihood and give a proof of the consiste...
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作者：Stute, W.; Xu, W. L.; Zhu, L. X.
作者单位：Justus Liebig University Giessen; Renmin University of China; Hong Kong Baptist University
摘要：We study tools for checking the validity of a parametric regression model. When the dimension of the regressors is large, many of the existing tests face the curse of dimensionality or require some ordering of the data. Our tests are based on the residual empirical process marked by proper functions of the regressors. They are able to detect local alternatives converging to the null at parametric rates. Parametric and nonparametric alternatives are considered. In the latter case, through a pro...
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作者：Ybarra, Lynn M. R.; Lohr, Sharon L.
作者单位：Arizona State University; Arizona State University-Tempe
摘要：Small area estimation methods typically combine direct estimates from a survey with predictions from a model in order to obtain estimates of population quantities with reduced mean squared error. When the auxiliary information used in the model is measured with error, using a small area estimator such as the Fay-Herriot estimator while ignoring measurement error may be worse than simply using the direct estimator. We propose a new small area estimator that accounts for sampling variability in ...
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作者：Hubbard, Alan E.; Van der Laan, Mark J.
作者单位：University of California System; University of California Berkeley
摘要：We propose a new causal parameter, which is a natural extension of existing approaches to causal inference such as marginal structural models. Modelling approaches are proposed for the difference between a treatment-specific counterfactual population distribution and the actual population distribution of an outcome in the target population of interest. Relevant parameters describe the effect of a hypothetical intervention on such a population and therefore we refer to these models as populatio...
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作者：Zhou, Lan; Huang, Jianhua Z.; Carroll, Raymond J.
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：We propose a modelling framework to study the relationship between two paired longitudinally observed variables. The data for each variable are viewed as smooth curves measured at discrete time-points plus random errors. While the curves for each variable are summarized using a few important principal components, the association of the two longitudinal variables is modelled through the association of the principal component scores. We use penalized splines to model the mean curves and the prin...
