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作者：Carone, Marco; Asgharian, Masoud; Jewell, Nicholas P.
作者单位：University of Washington; University of Washington Seattle; University of California System; University of California Berkeley; McGill University
摘要：Dementia is one of the world's major public health challenges. The lifetime risk of dementia is the proportion of individuals who ever develop dementia during their lifetime. Despite its importance to epidemiologists and policy-makers, this measure does not seem to have been estimated in the Canadian population. Data from a birth cohort study of dementia are not available. Instead, we must rely on data from the Canadian Study of Health and Aging, a large cross-sectional study of dementia with ...
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作者：Abadie, Alberto; Imbens, Guido W.; Zheng, Fanyin
作者单位：Harvard University; National Bureau of Economic Research; Stanford University; Harvard University
摘要：Following the work by Eicker, Huber, and White it is common in empirical work to report standard errors that are robust against general misspecification. In a regression setting, these standard errors are valid for the parameter that minimizes the squared difference between the conditional expectation and a linear approximation, averaged over the population distribution of the covariates. Here, we discuss an alternative parameter that corresponds to the approximation to the conditional expecta...
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作者：Ning, Jing; Qin, Jing; Shen, Yu
作者单位：University of Texas System; UTMD Anderson Cancer Center; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：The semiparametric accelerated failure time (AFT) model is one of the most popular models for analyzing time-to-event outcomes. One appealing feature of the AFT model is that the observed failure time data can be transformed to identically independent distributed random variables without covariate effects. We describe a class of estimating equations based on the score functions for the transformed data, which are derived from the full likelihood function under commonly used semiparametric mode...
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作者：Li, Bing; Chun, Hyonho; Zhao, Hongyu
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Purdue University System; Purdue University; Yale University
摘要：We introduce a nonparametric method for estimating non-Gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a...
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作者：Lindsay, Bruce G.; Markatou, Marianthi; Ray, Surajit
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; State University of New York (SUNY) System; University at Buffalo, SUNY; State University of New York (SUNY) System; University at Buffalo, SUNY; State University of New York (SUNY) System; University at Buffalo, SUNY; University of Glasgow
摘要：In this article, we study the power properties of quadratic-distance-based goodness-of-fit tests. First, we introduce the concept of a root kernel and discuss the considerations that enter the selection of this kernel. We derive an easy to use normal approximation to the power of quadratic distance goodness-of-fit tests and base the construction of a noncentrality index, an analogue of the traditional noncentrality parameter, on it. This leads to a method akin to the Neyman-Pearson lemma for c...
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作者：Zhu, Yunzhang; Shen, Xiaotong; Pan, Wei
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
摘要：Gaussian graphical models are useful to analyze and visualize conditional dependence relationships between interacting units. Motivated from network analysis under different experimental conditions, such as gene networks for disparate cancer subtypes, we model structural changes over multiple networks with possible heterogeneities. In particular, we estimate multiple precision matrices describing dependencies among interacting units through maximum penalized likelihood. Of particular interest ...
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作者：Aue, Alexander; Cheung, Rex C. Y.; Lee, Thomas C. M.; Zhong, Ming
作者单位：University of California System; University of California Davis
摘要：This article proposes new model-fitting techniques for quantiles of an observed data sequence, including methods for data segmentation and variable selection. The main contribution, however, is in providing a means to perform these two tasks simultaneously. This is achieved by matching the data with the best-fitting piecewise quantile regression model, where the fit is determined by a penalization derived from the minimum description length principle. The resulting optimization problem is solv...
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作者：Efron, Bradley
作者单位：Stanford University
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作者：Han, Fang; Liu, Han
作者单位：Johns Hopkins University; Princeton University
摘要：We propose a semiparametric method for conducting scale-invariant sparse principal component analysis (PCA) on high-dimensional non-Gaussian data. Compared with sparse PCA, our method has a weaker modeling assumption and is more robust to possible data contamination. Theoretically, the proposed method achieves a parametric rate of convergence in estimating the parameter of interests under a flexible semiparametric distribution family; computationally, the proposed method exploits a rank-based ...
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作者：Zeng, Donglin; Lin, D. Y.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：Under two-phase cohort designs, such as case-cohort and nested case-control sampling, information on observed event times, event indicators, and inexpensive covariates is collected in the first-phase, and the first-phase information is used to select subjects for measurements of expensive covariates in the second phase; inexpensive covariates are also used in the data analysis to control for confounding and to evaluate interactions. This article provides efficient estimation of semiparametric ...
