504期

最新文章

• A Marginal Approach to Reduced-Rank Penalized Spline Smoothing With Application to Multilevel Functional Data AI翻译
  作者：Chen, Huaihou; Wang, Yuanjia; Paik, Myunghee Cho; Choi, H. Alex
  作者单位：New York University; Columbia University; Seoul National University (SNU); University of Texas System; University of Texas Health Science Center Houston
  摘要：Multilevel functional data are collected in many biomedical studies. For example, in a study of the effect of Nimodipine on patients with subarachnoid hemorrhage (SAH), patients underwent multiple 4-hr treatment cycles. Within each treatment cycle, subjects' vital signs were reported every 10 min. These data have a natural multilevel structure with treatment cycles nested within subjects and measurements nested within cycles. Most literature on nonparametric analysis of suchmultilevel function...
• Two-Stage Importance Sampling With Mixture Proposals AI翻译
  作者：Li, Wentao; Tan, Zhiqiang; Chen, Rong
  作者单位：Lancaster University; Rutgers University System; Rutgers University New Brunswick
  摘要：For importance sampling (IS), multiple proposals can be combined to address different aspects of a target distribution. There are various methods for IS with multiple proposals, including Hesterberg's stratified IS estimator, Owen and Zhou's regression estimator, and Tan's maximum likelihood estimator. For the problem of efficiently allocating samples to different proposals, it is natural to use a pilot sample to select the mixture proportions before the actual sampling and estimation. However...
• Generalized Residuals for General Models for Contingency Tables With Application to Item Response Theory AI翻译
  作者：Haberman, Shelby J.; Sinharay, Sandip
  作者单位：Educational Testing Service (ETS)
  摘要：Generalized residuals are a tool employed in the analysis of contingency tables to examine possible sources of model error. They have typically been applied to log-linear models and to latent-class models. A general approach to generalized residuals is developed for a very general class of models for contingency tables. To illustrate their use, generalized residuals are applied to models based on item response theory (IRT) models. Such models are commonly applied to analysis of standardized ac...
• Bayesian Hierarchical Modeling of the HIV Evolutionary Response to Therapy AI翻译
  作者：Jensen, Shane T.; Park, Jared; Braunstein, Alexander F.; McAuliffe, Jon
  作者单位：University of Pennsylvania; University of California System; University of California Berkeley
  摘要：A major challenge for the treatment of human immunodeficiency virus (HIV) infection is the development of therapy-resistant strains. We present a statistical model that quantifies the evolution of HIV populations when exposed to particular therapies. A hierarchical Bayesian approach is used to estimate differences in rates of nucleotide changes between treatment- and control-group sequences. Each group's rates are allowed to vary spatially along the HIV genome. We employ a coalescent structure...
• A Progressive Block Empirical Likelihood Method for Time Series AI翻译
  作者：Kim, Young Min; Lahiri, Soumendra N.; Nordman, Daniel J.
  作者单位：Radiation Effects Research Foundation - Japan; North Carolina State University; Iowa State University
  摘要：This article develops a new blockwise empirical likelihood (BEL) method for stationary, weakly dependent time processes, called the progressive block empirical likelihood (PBEL). In contrast to the standard version of BEL, which uses data blocks of constant length for a given sample size and whose performance can depend crucially on the block length selection, this new approach involves a data-blocking scheme where blocks increase in length by an arithmetic progression. Consequently, no block ...
• Bayesian Modeling of Temporal Dependence in Large Sparse Contingency Tables AI翻译
  作者：Kunihama, Tsuyoshi; Dunson, David B.
  作者单位：Duke University
  摘要：It is of interest in many applications to study trends over time in relationships among categorical variables, such as age group, ethnicity, religious affiliation, political party, and preference for particular policies. At each time point, a sample of individuals provides responses to a set of questions, with different individuals sampled at each time. In such settings, there tend to be an abundance of missing data and the variables being measured may change over time. At each time point, we ...
• On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm AI翻译
  作者：Yang, Min; Biedermann, Stefanie; Tang, Elina
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; University of Southampton; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
  摘要：Finding optimal designs for nonlinear models is challenging in general. Although some recent results allow us to focus on a simple subclass of designs for most problems, deriving a specific optimal design still mainly depends on numerical approaches. There is need for a general and efficient algorithm that is more broadly applicable than the current state-of-the-art methods. We present a new algorithm that can be used to find optimal designs with respect to a broad class of optimality criteria...
• Resampling Procedures for Making Inference Under Nested Case-Control Studies AI翻译
  作者：Cai, Tianxi; Zheng, Yingye
  作者单位：Harvard University; Fred Hutchinson Cancer Center
  摘要：The nested case-control (NCC) design has been widely adopted as a cost-effective solution in many large cohort studies for risk assessment with expensive markers, such as the emerging biologic and genetic markers. To analyze data from NCC studies, conditional logistic regression and maximum likelihood-based methods have been proposed. However, most of these methods either cannot be easily extended beyond the Cox model or require additional modeling assumptions. More generally applicable approa...
• Epistatic Clustering: A Model-Based Approach for Identifying Links Between Clusters AI翻译
  作者：Zhang, Jian
  作者单位：University of Kent
  摘要：Most clustering methods assume that the data can be represented by mutually exclusive clusters, although this assumption may not be the case in practice. For example, in gene expression microarray studies, investigators have often found that a gene can play multiple functions in a cell and may, therefore, belong to more than one cluster simultaneously, and that gene clusters can be linked to each other in certain pathways. This article examines the effect of the above assumption on the likelih...
• Frailty Models for Familial Risk With Application to Breast Cancer AI翻译
  作者：Gorfine, Malka; Hsu, Li; Parmigiani, Giovanni
  作者单位：Technion Israel Institute of Technology; Fred Hutchinson Cancer Center; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：In evaluating familial risk for disease we have two main statistical tasks: assessing the probability of carrying an inherited genetic mutation conferring higher risk, and predicting the absolute risk of developing diseases over time for those individuals whose mutation status is known. Despite substantial progress, much remains unknown about the role of genetic and environmental risk factors, about the sources of variation in risk among families that carry high-risk mutations, and about the s...