2012

最新文章

• A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error AI翻译
  作者：Yi, Grace Y.; Ma, Yanyuan; Carroll, Raymond J.
  作者单位：University of Waterloo; Texas A&M University System; Texas A&M University College Station
  摘要：Covariate measurement error and missing responses are typical features in longitudinal data analysis. There has been extensive research on either covariate measurement error or missing responses, but relatively little work has been done to address both simultaneously. In this paper, we propose a simple method for the marginal analysis of longitudinal data with time-varying covariates, some of which are measured with error, while the response is subject to missingness. Our method has a number o...
• An efficient method of estimation for longitudinal surveys with monotone missing data AI翻译
  作者：Zhou, Ming; Kim, Jae Kwang
  作者单位：Iowa State University
  摘要：Panel attrition is frequently encountered in panel sample surveys. When it is related to the observed study variable, the classical approach of nonresponse adjustment using a covariate-dependent dropout mechanism can be biased. We consider an efficient method of estimation with monotone panel attrition when the response probability depends on the previous values of study variable as well as other covariates. Because of the monotone structure of the missing pattern, the response mechanism is mi...
• On the robustness of the adaptive lasso to model misspecification AI翻译
  作者：Lu, W.; Goldberg, Y.; Fine, J. P.
  作者单位：North Carolina State University; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Penalization methods have been shown to yield both consistent variable selection and oracle parameter estimation under correct model specification. In this article, we study such methods under model misspecification, where the assumed form of the regression function is incorrect, including generalized linear models for uncensored outcomes and the proportional hazards model for censored responses. Estimation with the adaptive least absolute shrinkage and selection operator, lasso, penalty is pr...
• Penalized empirical likelihood and growing dimensional general estimating equations AI翻译
  作者：Leng, Chenlei; Tang, Cheng Yong
  作者单位：National University of Singapore
  摘要：When a parametric likelihood function is not specified for a model, estimating equations may provide an instrument for statistical inference. Qin and Lawless (1994) illustrated that empirical likelihood makes optimal use of these equations in inferences for fixed low-dimensional unknown parameters. In this paper, we study empirical likelihood for general estimating equations with growing high dimensionality and propose a penalized empirical likelihood approach for parameter estimation and vari...
• Quadratic inference function approach to merging longitudinal studies: validation and joint estimation AI翻译
  作者：Wang, Fei; Wang, Lu; Song, Peter X. -K.
  作者单位：University of Michigan System; University of Michigan
  摘要：Merging data from multiple studies has been widely adopted in biomedical research. In this paper, we consider two major issues related to merging longitudinal datasets. We first develop a rigorous hypothesis testing procedure to assess the validity of data merging, and then propose a flexible joint estimation procedure that enables us to analyse merged data and to account for different within-subject correlations and follow-up schedules in different studies. We establish large sample propertie...