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作者：Parast, Layla; Cheng, Su-Chun; Cai, Tianxi
作者单位：RAND Corporation; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
摘要：In recent years, a wide range of markers have become available as potential tools to predict risk or progression of disease. In addition to such biological and genetic markers, short-term outcome information may be useful in predicting long-term disease outcomes. When such information is available, it would be desirable to combine this along with predictive markers to improve the prediction of long-term survival. Most existing methods for incorporating censored short-term event information in ...
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作者：Davies, P. L.
作者单位：University of Duisburg Essen
摘要：The standard model for the analysis of variance is over-parameterized. The resulting identifiability problem is typically solved by placing linear constraints on the parameters. In the case of the interactions, these require that the marginal sums be zero. Although seemingly neutral, these conditions have unintended consequences: the interactions are of necessity connected whether or not this is justified, the minimum number of nonzero interactions is four, and, in particular, it is not possib...
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作者：Dukic, Vanja; Lopes, Hedibert F.; Polson, Nicholas G.
作者单位：University of Colorado System; University of Colorado Boulder; University of Chicago
摘要：In this article, we use Google Flu Trends data together with a sequential surveillance model based on state-space methodology to track the evolution of an epidemic process over time. We embed a classical mathematical epidemiology model [a susceptible-exposed-infected-recovered (SEIR) model] within the state-space framework, thereby extending the SEW dynamics to allow changes through time. The implementation of this model is based on a particle filtering algorithm, which learns about the epidem...
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作者：Clarke, Paul S.; Windmeijer, Frank
作者单位：University of Bristol; University of Bristol; University of Bristol
摘要：Instrumental variables (IVs) can be used to construct estimators of exposure effects on the outcomes of studies affected by nonignorable selection of the exposure. Estimators that fail to adjust for the effects of nonignorable selection will be biased and inconsistent. Such situations commonly arise in observational studies, but are also a problem for randomized experiments affected by nonignorable noncompliance. In this article, we review IV estimators for studies in which the outcome is bina...
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作者：Telesca, Donatello; Mueller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan
作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of Texas System; University of Texas Austin; University of Texas System; UTMD Anderson Cancer Center
摘要：High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying...
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作者：Wang, Huixia Judy; Li, Deyuan; He, Xuming
作者单位：North Carolina State University; Fudan University; University of Michigan System; University of Michigan
摘要：Estimation of conditional quantiles at very high or low tails is of interest in numerous applications. Quantile regression provides a convenient and natural way of quantifying the impact of covariates at different quantiles of a response distribution. However, high tails are often associated with data sparsity, so quantile regression estimation can suffer from high variability at tails especially for heavy-tailed distributions. In this article, we develop new estimation methods for high condit...
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作者：Wang, Yuanjia; Garcia, Tanya P.; Ma, Yanyuan
作者单位：Columbia University; Texas A&M University System; Texas A&M University College Station
摘要：This work presents methods for estimating genotype-specific outcome distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estima...
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作者：Killick, R.; Fearnhead, P.; Eckley, I. A.
作者单位：Lancaster University
摘要：In this article, we consider the problem of detecting multiple changepoints in large datasets. Our focus is on applications where the number of changepoints will increase as we collect more data: for example, in genetics as we analyze larger regions of the genome, or in finance as we observe time series over longer periods. We consider the common approach of detecting changepoints through minimizing a cost function over possible numbers and locations of changepoints. This includes several esta...
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作者：Xue, Lingzhou; Ma, Shiqian; Zou, Hui
作者单位：Princeton University; Chinese University of Hong Kong; University of Minnesota System; University of Minnesota Twin Cities
摘要：The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis. To fix this drawback of thresholding estimation, we develop a positive-definite l(1)-penalized covariance estimator for estimating sparse large covariance matrices. We derive an efficient alternating direction method to solve the challenging optimization problem and establish its convergence properties. Unde...
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作者：La Vecchia, Davide; Ronchetti, Elvezio; Trojani, Fabio
作者单位：Monash University; University of Geneva; University of Geneva; Universita della Svizzera Italiana; Swiss Finance Institute (SFI)
摘要：Using the von Mises expansion, we study the higher-order infinitesimal robustness of a general M-functional and characterize its second-order properties. We show that second-order robustness is equivalent to the boundedness of both the estimator's estimating function and its derivative with respect to the parameter. It implies, at the same time, (i) variance robustness and (ii) robustness of higher-order saddlepoint approximations to the estimator's finite sample density. The proposed construc...
