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作者：Shepherd, Bryan E.; Redman, Mary W.; Ankerst, Donna R.
作者单位：Vanderbilt University; Technical University of Munich
摘要：In 2003 Thompson and colleagues reported that daily use of finasteride reduced the prevalence of prostate cancer by 25% compared to placebo. These results were based oil the double-blind randomized Prostate Cancer Prevention Trial (PCPT), which followed 18.882 men with no prior Or Current indications of prostate cancer annually for 7 years. Enthusiasm for the risk reduction afforded by the chemopreventative agent and adoption Of its use in clinical practice. however. was severely dampened by (...
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作者：Huang, Chiung-Yu; Qin, Jing; Follmann, Dean A.
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：The pretest-posttest study design is commonly used in medical and social science research to assess the effect of a treatment or an intervention. Recently, interest has been rising in developing inference procedures that improve efficiency while relaxing assumptions used in the pretest-posttest data analysis, especially when the posttest measurement might be missing. In this article we propose a semiparametric estimation procedure based on empirical likelihood (EL) that incorporates the common...
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作者：Mueller, Peter; Nieto-Barajas, Luis
作者单位：University of Texas System; UTMD Anderson Cancer Center; Instituto Tecnologico Autonomo de Mexico
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作者：Kim, Yongdai; Choi, Hosik; Oh, Hee-Seok
作者单位：Seoul National University (SNU); Hoseo University
摘要：The smoothly clipped absolute deviation (SCAD) estimator, proposed by Fan and Li, has many desirable properties, including continuity, sparsity, and unbiasedness. The SCAD estimator also has the (asymptotically) oracle property when the dimension of covariates is fixed or diverges more slowly than the sample size. In this article we study the SCAD estimator in high-dimensional settings where the dimension of covariates can be much larger than the sample size. First, we develop and efficient op...
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作者：Xia, Yingcun
作者单位：National University of Singapore
摘要：Dimension reduction can be used as an initial step in statistical modeling. Further specification of model structure is imminent and important when the reduced dimension is still greater than 1. In this article we investigate one method of specification that involves separating the linear component front the nonlinear components, leading to further dimension reduction in the unknown link function and. thus, better estimation and easier interpretation of the model. The specified Model includes ...
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作者：Johnson, Brent A.; Lin, D. Y.; Zeng, Donglin
作者单位：Emory University; University of North Carolina; University of North Carolina Chapel Hill
摘要：We propose a general strategy for variable selection in semiparametric regression models by penalizing appropriate estimating functions. Important applications include semiparametric linear regression with censored responses and semiparametric regression with missing predictors. Unlike the existing penalized maximum likelihood estimators, the proposed penalized estimating functions may not pertain to the derivatives of any objective functions and may be discrete in the regression coefficients....
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作者：Qin, Jing; Shao, Jun; Zhang, Biao
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); University of Wisconsin System; University of Wisconsin Madison; University System of Ohio; University of Toledo
摘要：In this article we study a well-known response missing-data problem. Missing data is an ubiquitous problem in medical and social science studies. Imputation is one of the most popular methods for dealing with missing data. The most commonly used imputation that makes use of covariates is regression imputation, in which the regression model can be parametric, semiparametric, or nonparametric. Parametric regression imputation is efficient but is not robust against misspecification of the regress...
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作者：Shi, Tao; Yu, Bin; Clothiaux, Eugene E.; Braverman, Amy J.
作者单位：University System of Ohio; Ohio State University; University of California System; University of California Berkeley; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; National Aeronautics & Space Administration (NASA); NASA Jet Propulsion Laboratory (JPL); California Institute of Technology
摘要：Global climate models predict that the strongest dependences of surface air temperatures on increasing atmospheric carbon dioxide levels will occur in the Arctic. A systematic study of these dependences requires accurate Arctic-wide measurements, especially of cloud coverage. Thus cloud detection in the Arctic is extremely important, but it is also challenging because of the similar remote sensing characteristics of clouds and ice- and snow-covered surfaces. This article proposes two new opera...
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作者：Dong, Yuping; Hedayat, A. S.; Sinha, B. K.
作者单位：Bristol-Myers Squibb; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Indian Statistical Institute; Indian Statistical Institute Kolkata
摘要：Surveillance is a major issue in the today's world. The need to develop adequate surveillance strategies is genuine in many spheres of human activity. In this article we focus on a specific problem of surveillance and discuss some related statistical issues. This specific problem deals with a possible change in the incidence rate of an event (to a higher value) when a system is studied at discrete time points. We apply the exponentially weighted moving average methods for detecting an increase...
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作者：Ibrahim, Joseph G.; Zhu, Hongtu; Tang, Niansheng
作者单位：University of North Carolina; University of North Carolina Chapel Hill; Yunnan University
摘要：We consider novel methods for the Computation of model selection criteria in missing-data problems based on the output of the EM algorithm The methodology is very general and can be applied to numerous simulations involving incomplete data within an EM framework, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Toward this goal, we develop a class of information criteria for missing-data problems called ICH,Q, wh...
