Journal of the American Statistical Association

最新文章

• Hidden Markov models and disease mapping AI翻译
  作者：Green, PJ; Richardson, S
  作者单位：University of Bristol; Imperial College London
  摘要：We present new methodology to extend hidden Markov models to the spatial domain, and use this class of models to analyze spatial heterogeneity of count data on a rare phenomenon. This situation occurs commonly in many domains of application, particularly in disease mapping. We assume that the counts follow a Poisson model at the lowest level of the hierarchy, and introduce a finite-mixture model for the Poisson rates at the next level. The novelty lies in the model for allocation to the mixtur...
• Latent class analysis of complex sample survey data: Application to dietary data AI翻译
  作者：Patterson, BH; Dayton, CM; Graubard, B
  作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); University System of Maryland; University of Maryland College Park; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics
  摘要：High fruit and vegetable intake is associated with decreased cancer risk. However, dietary recall data from national surveys suggest that, on any given day, intake falls below the recommended minima of three daily servings of vegetables and two daily servings of fruit. There is no single widely accepted measure of usual intake. One approach is to regard the distribution of intake as a mixture of regular (relatively frequent) and nonregular (relatively infrequent) consumers, using an indicator ...
• Locally efficient estimation of a multivariate survival function in longitudinal studies AI翻译
  作者：van der Laan, MJ; Hubbard, AE; Robins, JM
  作者单位：University of California System; University of California Berkeley; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：We consider estimation of the joint distribution of multivariate survival times T = (T-1,...,T-k), which are subject to right-censoring by a common censoring variable C. Two estimators are proposed: an initial inverse-probability-of-censoring weighted (IPCW) estimator and a one-step estimator. Both estimators incorporate information on available time-independent and time-dependent prognostic factor (covariate) data. The IPCW estimator is consistent and asymptotically normal (CAN) under coarsen...
• Nearest-neighbor variance estimation (NNVE): Robust covariance estimation via nearest-neighbor cleaning - Comment AI翻译
  作者：McLachlan, GJ; Hamaty, KL
  作者单位：University of Queensland
• Statistical bridges AI翻译
  作者：Scheaffer, RL
  作者单位：State University System of Florida; University of Florida
  摘要：In the information age of today, statistics is essential but statisticians are not. Yet statisticians have much to offer and must be proactive in their approaches to leaders in education, producers and users of data, the scientific community of scholars, and the public at large. Properly constructed bridges to these constituencies can convey the positive contributions of statistical thinking for all, strong academic programs in statistics, the value-added practice of statistics, and the infusi...
• A nonparametric test of gene region heterogeneity associated with phenotype AI翻译
  作者：Kowalski, J; Pagano, M; DeGruttola, V
  作者单位：Johns Hopkins University; Johns Hopkins University; Harvard University
  摘要：High-dimensional statistical problems arise in the investigation of the relationship between reduced sensitivity to antiretroviral drugs among human immunodeficiency virus-infected patients and viral genotypic patterns obtained from blood samples, This article develops a nonparametric approach for analyzing gene region heterogeneity associated with drug-resistance phenotype, The method is based on the distribution of distances between viral genetic sequences. The distance measures used are suf...
• Modeling regression error with a mixture of Polya trees AI翻译
  作者：Hanson, T; Johnson, WO
  作者单位：University of New Mexico; University of California System; University of California Davis
  摘要：We model the error distribution in the standard linear model as a mixture of absolutely continuous Polya trees constrained to have median 0. By considering a mixture, we smooth out the partitioning effects of a simple Polya tree and the predictive error density has a derivative everywhere except 0. The error distribution is centered around a standard parametric family of distributions and thus may be viewed as a generalization of standard models in which important, data-driven features, such a...
• Predictive variable selection in generalized linear models AI翻译
  作者：Meyer, MC; Laud, PW
  作者单位：University System of Georgia; University of Georgia; Medical College of Wisconsin
  摘要：Here we extend predictive method for model selection of Laud and Ibrahim to the generalized linear model. This prescription avoids the need to directly specify prior probabilities of models and prior densities for the parameters. Instead, a prior prediction for the response induces the required priors. We propose normal and conjugate priors for generalized linear models, each using a single prior prediction for the mean response to induce suitable priors for each variable-subset model. In this...
• Calibration regression of censored lifetime medical cost (vol 97, pg 318) AI翻译
  作者：Huang, YJ
• Bayesian methods for hidden Markov models: Recursive computing in the 21st century AI翻译
  作者：Scott, SL
  作者单位：University of Southern California
  摘要：Markov chain Monte Carlo (MCMC) sampling strategies can be used to simulate hidden Markov model (HMM) parameters from their posterior distribution given observed data, Some MCMC methods used in practice (for computing likelihood, conditional probabilities of hidden states, and the most likely sequence of states) can be improved by incorporating established recursive algorithms. The most important of these is a set of forward-backward recursions calculating conditional distributions of the hidd...