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作者：Gianola, D
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
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作者：Thomas, DC
作者单位：University of Southern California
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作者：Natarajan, R; Kass, RE
作者单位：State University System of Florida; University of Florida; Carnegie Mellon University
摘要：Bayesian methods furnish an attractive approach to inference in generalized linear mixed models. In the absence of subjective prior information for the random-effect variance components, these analyses are typically conducted using either the standard invariant prior for normal responses or diffuse conjugate priors. Previous work has pointed out serious difficulties with both strategies, and we show here that as in normal mixed models, the standard invariant prior leads to an improper posterio...
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作者：Serroukh, A; Walden, AT; Percival, CB
作者单位：Imperial College London; University of Washington; University of Washington Seattle
摘要：Many physical processes are an amalgam of components operating on different scales, and scientific questions about observed data are often inherently linked to understanding the behavior at different scales. We explore time-scale properties of time series through the variance at different scales derived using wavelet methods. The great advantage of wavelet methods over ad hoc modifications of existing techniques is that wavelets provide exact scale-based decomposition results. We consider proc...
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作者：Beran, R
作者单位：University of California System; University of California Berkeley
摘要：REACT estimators for the mean of a linear model involve three steps: transforming the model to a canonical form that provides an economical representation of the unknown mean vector, estimating the risks of a class of candidate linear shrinkage estimators, and adaptively selecting the candidate estimator that minimizes estimated risk. Applied to one- or higher-way layouts, the REACT method generates automatic scatterplot smoothers that compete well on standard datasets with the best fits obtai...
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作者：Greenland, S
作者单位：University of California System; University of California Los Angeles
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作者：Harrington, DP
作者单位：Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
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作者：Guttorp, P
作者单位：University of Washington; University of Washington Seattle
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作者：Spiegelman, D; Rosner, B; Logan, R
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital
摘要：In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression model to represent the relationship between the binary outcome and the perfectly measured and classified covariates, the model for the observed main study data is derived. This derivation relies on the assumption that the error in the continuous covariates is multivariate normally distributed and uses a chain of logistic regression mo...
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作者：Duval, S; Tweedie, R
作者单位：Colorado State University System; Colorado State University Fort Collins; University of Minnesota System; University of Minnesota Twin Cities
摘要：Meta-analysis collects and synthesizes results from individual studies to estimate an overall effect size. If published studies are chosen, say through a literature review, then an inherent selection bias may arise, because, for example, studies may tend to be published more readily if they are statistically significant, or deemed to be more interesting in terms of the impact of their outcomes. We develop a simple rank-based data augmentation technique, formalizing the use of funnel plots, to ...
