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作者：Rothman, Adam J.; Levina, Elizaveta; Zhu, Ji
作者单位：University of Michigan System; University of Michigan
摘要：We propose a new class of generalized thresholding operators that combine thresholding with shrinkage, and Study generalized thresholding of the sample covariance matrix in high dimensions. Generalized thresholding of the covariance matrix has good theoretical properties and carries almost no computational burden. We obtain in explicit convergence rate in the operator norm that shows the tradeoff between the sparsity of the true model, dimension, and the sample size, and shows that generalized...
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作者：Wikle, C. K.; Milliff, R. F.
作者单位：University of Missouri System; University of Missouri Columbia; NorthWest Research Associates
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作者：Peng, Limin; Fine, Jason P.
作者单位：Emory University; Rollins School Public Health; University of North Carolina; University of North Carolina Chapel Hill
摘要：Quantile regression has emerged as a significant extension of traditional linear models and its potential in survival applications has recently been recognized. In this paper we study quantile regression with competing risks data, formulating the model based on conditional quantiles defined using the cumulative incidence function, which includes as a special case an analog to the usual accelerated failure time model. The proposed competing risks quantile regression model provides meaningful ph...
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作者：Huang, Lan; Tiwari, Ram C.; Zou, Zhaohui; Kulldorff, Martin; Feuer, Eric J.
作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH Division of Cancer Control & Population Sciences; US Food & Drug Administration (FDA); Information Management Services, Inc.; Harvard University; Harvard Medical School; Harvard Pilgrim Health Care
摘要：In geographical spatial epidemiology and disease surveillance, all the existing spatial scan methods for cluster detection using continuous data are designed for evaluating clusters of individuals and analyzing individual-level data. Motivated by growing demands to study the spatial heterogeneity of continuous measures in population data, such as mortality rates, survival rates, average body mass indexes and pollution at state, county, and census tract levels. we propose a weighted normal scan...
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作者：Wang, Hansheng; Tsai, Chih-Ling
作者单位：Peking University; University of California System; University of California Davis
摘要：In extreme value statistics, the tail index is an important measure to gauge the heavy-tailed behavior of a distribution, Under Pareto-type distributions, we employ the logarithmic function to link the tail index to the linear predictor induced by covariates, which constitutes the tail index regression model. We then propose an approximate log-likelihood function to obtain regression parameter estimators, and Subsequently show the asymptotic normality of those estimators. Numerical studies are...
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作者：Qin, Jing; Zhang, Biao; Leung, Denis H. Y.
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); University System of Ohio; University of Toledo; Singapore Management University
摘要：Missing data is a ubiquitous problem in medical and social sciences. It is well known that inferences based only on the complete data may not only lose efficiency, but may also lead to biased results if the data is not missing completely at random (MCAR). The inverse-probability weighting method proposed by Horvitz and Thompson (1952) is a popular alternative when the data is not MCAR. The Horvitz-Thompson method, however, is sensitive to the inverse weights and may suffer from loss of efficie...
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作者：Cheng, Ming-Yen; Zhang, Wenyang; Chen, Lu-Hung
作者单位：National Taiwan University; University of London; University College London; University of Bath
摘要：Multiparameter likelihood models (MLMs) with multiple covariates have a wide range of applications: however. they encounter the curse of dimensionality problem when the dimension of the covariates is large. We develop a generalized multiparameter likelihood model that copes with multiple covariates and adapts to dynamic structural changes well. It includes some popular models, such as the partially linear and varying-coefficient models, as special cases. We present a simple, effective two-step...
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作者：Nettleton, Dan
作者单位：Iowa State University
摘要：Tests for the supremacy of a multinomial cell probability are developed. The tested null hypothesis states that a particular cell of interest is not more probable than all others, Rejection of this null leads to the conclusion that the cell of interest has a strictly greater probability than all other cells. The null hypothesis constrains the multinomial probability vector to a nonconvex region that is a union of closed convex cones. The likelihood ratio test for this problem is derived and sh...
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作者：Othus, Megan; Li, Yi; Tiwari, Ram C.
作者单位：Harvard University; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; US Food & Drug Administration (FDA); National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
摘要：Modern cancer treatments have substantially improved cure rates and have generated a great interest in and need for proper statistical tools to analyze survival data with nonnegligible cure fractions. Data with Cure fractions often ire complicated by dependent censoring, and the analysis of this type of data typically involves untestable parametric assumptions on the dependence of the censoring mechanism and the true survival times. Motivated by the analysis of prostate cancer survival trends,...
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作者：Norton, Jonathan D.; Niu, Xu-Feng
作者单位：US Food & Drug Administration (FDA); State University System of Florida; Florida State University
摘要：A class of hierarchical Bayesian models is proposed for adverse birth outcomes such as preterm birth, which are conditional binomial distribution. The log-odds of an adverse outcome in a particular county, logit(p(i)), follow a linear model that includes observed covariates and normally-distributed random effects. Spatial dependence between neighboring regions is allowed for by including an intrinsically autoregressive (IAR) prior or air IAR convolution prior in the linear predictor. Temporal ...
