474期

最新文章

• Large-sample joint posterior approximations when full conditionals are approximately normal: Application to generalized linear mixed models AI翻译
  作者：Su, Chun-Lung; Johnson, Wesley O.
  作者单位：University of California System; University of California Davis; University of California System; University of California Irvine
  摘要：Modern Bayesian statistical methods, such as Gibbs and Metropolis-Hastings sampling, were developed to liberate statisticians from the necessity of making large-sample assumptions and to facilitate the numerical approximation of problems that had previously been analytically intractable. Counter to this trend, we develop a method for constructing asymptotic joint posterior approximations based on models with k blocks of parameters and where the corresponding properly normalized full conditiona...
• A Bayesian approach for clustered longitudinal ordinal outcome with nonignorable missing data: Evaluation of an asthma education program AI翻译
  作者：Kaciroti, Niko A.; Raghunathan, Trivellore E.; Schork, M. Anthony; Clark, Noreen M.; Gong, Molly
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Asthma, a chronic inflammatory disease of the airways, affects an estimated 6.3 million children under age 18 in the United States. A key to successful asthma management, and hence improved quality of life (QOL), calls for an active partnership between asthma patients and their health care providers. To foster this partnership, an intervention program was designed and evaluated using a randomized longitudinal study. The study focused on several outcomes where typically missing data remained a ...
• On the large-sample minimal coverage probability of confidence intervals after model selection AI翻译
  作者：Kabaila, Paul; Leeb, Hannes
  作者单位：La Trobe University; Yale University
  摘要：We give a large-sample analysis of the minimal coverage probability of the usual confidence intervals for regression parameters when the underlying model is chosen by a conservative (or overconsistent) model selection procedure. We derive an upper bound for the large-sample limit minimal coverage probability of such intervals that applies to a large class of model selection procedures including the Akaike information criterion as well as various pretesting procedures. This upper bound can be u...
• Semiparametric transformation models for survival data with a cure fraction AI翻译
  作者：Zeng, Donglin; Yin, Guosheng; Ibrahim, Joseph G.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Texas System; UTMD Anderson Cancer Center
  摘要：We propose a class of transformation models for survival data with a cure fraction. The class of transformation models is motivated by biological considerations and includes both the proportional hazards and the proportional odds cure models as two special cases. An efficient recursive algorithm is proposed to calculate the maximum likelihood estimators (MLEs). Furthermore, the MLEs for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic varia...
• Estimating mean dimensionality of analysis of variance decompositions AI翻译
  作者：Liu, Ruixue; Owen, Art B.
  作者单位：Stanford University
  摘要：Analysis of variance (ANOVA) is now often applied to functions defined on the unit cube, where it serves as a tool for the exploratory analysis of functions. The mean dimension of a function, defined as a natural weighted combination of its ANOVA mean squares, provides one measure of how hard or easy it is to integrate the function by quasi-Monte Carlo sampling. This article presents some new identities relating the mean dimension, and some analogously defined higher moments, to the variance i...
• Multicategory Ψ-learning AI翻译
  作者：Liu, Yufeng; Shen, Xiaotong
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Minnesota System; University of Minnesota Twin Cities
  摘要：In binary classification, margin-based techniques usually deliver high performance. As a result, a multicategory problem is often treated as a sequence of binary classifications. In the absence of a dominating class, this treatment may be suboptimal and may yield poor performance, such as for support vector machines (SVMs). We propose a novel multicategory generalization of psi-learning that treats all classes simultaneously. The new generalization eliminates this potential problem while at th...
• Specifying and implementing nonparametric and semiparametric survival estimators in two-stage (nested) cohort studies with missing case data AI翻译
  作者：Mark, Steven D.; Katki, Hormuzd A.
  作者单位：University of Colorado System; University of Colorado Anschutz Medical Campus; University of Colorado Denver; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics
  摘要：Since 1986, we have been studying a cohort of individuals from a region in China with epidemic rates of gastric cardia cancer and have conducted numerous two-stage studies to assess the association of various exposures with this cancer. Two-stage studies are a commonly used statistical design. Stage one involves observing the outcomes and accessible baseline covariate information on all cohort members, and stage two involves using the stage one observations to select a subset of the cohort for...
• Bayesian sample size determination for case-control studies AI翻译
  作者：M'Lan, Cyr Emile; Joseph, Lawrence; Wolfson, David B.
  作者单位：University of Connecticut; McGill University; McGill University
  摘要：Case-control studies are among the most commonly used means of assessing association between exposure and outcome. Sample size determination and the optimal control-to-case ratio are vital to the design of such studies. In this article we investigate Bayesian sample size determination and the control-to-case ratio for case-control studies, when interval estimation is the goal of the eventual statistical analysis. In certain cases we are able to derive approximate closed-form sample size formul...
• A class of latent marginal models for capture-recapture data with continuous covariates AI翻译
  作者：Bartolucci, Francesco; Forcina, Antonio
  作者单位：University of Perugia
  摘要：We introduce a new family of latent class models for the analysis of capture-recapture data where continuous covariates are available. The present approach exploits recent advances in marginal parameterizations to model simultaneously, and conditionally on individual covariates, the size of the latent classes, the marginal probabilities of being captured by each list given the latent, and possible higher-order marginal interactions among lists conditionally on the latent. An EM algorithm for m...
• On the correlation matrix of the discrete Fourier transform and the fast solution of large Toeplitz systems for long-memory time series AI翻译
  作者：Chen, Willa W.; Hurvich, Clifford M.; Lu, Yi
  作者单位：Texas A&M University System; Texas A&M University College Station; New York University
  摘要：We show that for long-memory time series, the Toeplitz system Sigma(n)(f)x = b can be solved in O(n log(5/2) n) operations using a well-known version of the preconditioned conjugate gradient method, where Sigma(n)(f) is the n x n covariance matrix, f is the spectral density, and b is a known vector. Solutions of such systems are needed for optimal linear prediction and interpolation. We establish connections between this preconditioning method and the frequency domain analysis of time series. ...