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作者：Ye, Ting; Small, Dylan S.; Rosenbaum, Paul R.
作者单位：University of Washington; University of Washington Seattle; University of Pennsylvania
摘要：Many observational studies assess the impact of a treatment on an outcome that has several dimensions. In the observational study that we discuss, physical abuse of children may affect the degree to which the child exhibits depression, withdrawal or aggression. A treatment may affect all, some or none of these dimensions. In addition to the scientific interest in learning the effect on each dimension, it is also known that an appropriate combination of dimensions may increase power, efficiency...
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作者：Hector, Emily C.; Song, Peter X-K
作者单位：North Carolina State University; University of Michigan System; University of Michigan
摘要：We propose a distributed quadratic inference function framework to jointly estimate regression parameters from multiple potentially heterogeneous data sources with correlated vector outcomes. The primary goal of this joint integrative analysis is to estimate covariate effects on all outcomes through a marginal regression model in a statistically and computationally efficient way. We develop a data integration procedure for statistical estimation and inference of regression parameters that is i...
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作者：Masci, Chiara; Ieva, Francesca; Paganoni, Anna Maria
作者单位：Polytechnic University of Milan
摘要：Many applicative studies deal with multinomial responses and hierarchical data. Performing clustering at the highest level of grouping, in multilevel multinomial regression, is also often of interest. In this study we analyse Politecnico di Milano data with the aim of profiling students, modelling their probabilities of belonging to different categories and considering their nested structure within engineering degree programmes. In particular, we are interested in clustering degree programmes ...
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作者：Mews, Sina; Langrock, Roland; King, Ruth; Quick, Nicola
作者单位：University of Bielefeld; University of Edinburgh; University of St Andrews
摘要：Multistate capture-recapture data comprise individual-specific sighting histories, together with information on individuals' states related, for example, to breeding status, infection level, or geographical location. Such data are often analysed using the Arnason-Schwarz model, where transitions between states are modelled using a discrete-time Markov chain, making the model most easily applicable to regular time series. When time intervals between capture occasions are not of equal length, mo...
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作者：Tveten, Martin; Eckley, Idris A.; Fearnhead, Paul
作者单位：University of Oslo; Lancaster University
摘要：Motivated by a condition monitoring application arising from subsea engineering, we derive a novel, scalable approach to detecting anomalous mean structure in a subset of correlated multivariate time series. Given the need to analyse such series efficiently, we explore a computationally efficient approximation of the maximum likelihood solution to the resulting modelling framework and develop a new dynamic programming algorithm for solving the resulting binary quadratic programme when the prec...
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作者：Wang, Jianqiao; Wang, Wanjie; Li, Hongzhe
作者单位：University of Pennsylvania; National University of Singapore
摘要：Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) that are associated with complex traits. GWAS data allows us to investigate the shared genetic etiologies among different traits. However, linkage disequilibrium (LD) between the SNPs complicates the detection and identification of shared genetic effects. In this paper we model the LD by dividing the genome into LD blocks and linking the genetic variants within a block to a possible laten...
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作者：Russo, Massimiliano; Singer, Burton H.; Dunson, David B.
作者单位：Harvard University; Harvard Medical School; State University System of Florida; University of Florida; State University System of Florida; University of Florida; Duke University
摘要：Characterizing the shared memberships of individuals in a classification scheme poses severe interpretability issues, even when using a moderate number of classes (say four). Mixed membership models quantify this phenomenon, but they typically focus on goodness-of-fit more than on interpretable inference. To achieve a good numerical fit, these models may, in fact, require many extreme profiles, making the results difficult to interpret. We introduce a new class of multivariate mixed membership...
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作者：Zhou, Ling; Sun, Shiquan; Fu, Haoda; Song, Peter X-K
作者单位：Southwestern University of Finance & Economics - China; Xi'an Jiaotong University; Eli Lilly; University of Michigan System; University of Michigan
摘要：The emerging field of precision medicine is transforming statistical analysis from the classical paradigm of population-average treatment effects into that of personal treatment effects. This new scientific mission has called for adequate statistical methods to assess heterogeneous covariate effects in regression analysis. This paper focuses on a subgroup analysis that consists of two primary analytic tasks: identification of treatment effect subgroups and individual group memberships, and sta...
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作者：Belzile, Leo R.; Davison, Anthony C.
作者单位：Universite de Montreal; HEC Montreal; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：We discuss the use of likelihood asymptotics for inference on risk measures in univariate extreme value problems, focusing on estimation of high quantiles and similar summaries of risk for uncertainty quantification. We study whether higher-order approximation, based on the tangent exponential model, can provide improved inferences. We conclude that inference based on maxima is generally robust to mild model misspecification and that profile likelihood-based confidence intervals will often be ...
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作者：Huang, Ying; Zhuang, Yingying; Gilbert, Peter
作者单位：Fred Hutchinson Cancer Center
摘要：This article addresses the evaluation of postrandomization immune response biomarkers as principal surrogate endpoints of a vaccine's protective effect, based on data from randomized vaccine trials. An important metric for quantifying a biomarker's principal surrogacy in vaccine research is the vaccine efficacy curve, which shows a vaccine's efficacy as a function of potential biomarker values if receiving vaccine, among an early-always-at-risk principal stratum of trial participants who remai...
