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作者：Cai, Tianxi; Liu, Molei; Xia, Yin
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Fudan University
摘要：Evidence-based decision making often relies on meta-analyzing multiple studies, which enables more precise estimation and investigation of generalizability. Integrative analysis of multiple heterogeneous studies is, however, highly challenging in the ultra high-dimensional setting. The challenge is even more pronounced when the individual-level data cannot be shared across studies, known as DataSHIELD contraint. Under sparse regression models that are assumed to be similar yet not identical ac...
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作者：Lyu, Ziyang; Welsh, A. H.
作者单位：University of Queensland; Australian National University
摘要：In this article we derive the asymptotic distribution of estimated best linear unbiased predictors (EBLUPs) of the random effects in a nested error regression model. Under very mild conditions which do not require the assumption of normality, we show that asymptotically the distribution of the EBLUPs as both the number of clusters and the cluster sizes diverge to infinity is the convolution of the true distribution of the random effects and a normal distribution. This result yields very simple...
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作者：Allen, David E.; McAleer, Michael
作者单位：University of Sydney; Asia University Taiwan; Edith Cowan University; Asia University Taiwan; University of Sydney; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam; Complutense University of Madrid; Complutense University of Madrid; University of Canterbury; Yokohama National University
摘要：This note comments on the generalized measure of correlation (GMC) that was suggested by Zheng, Shi, and Zhang. The GMC concept was partly anticipated in some publications over 100 years earlier by Yule in the Proceedings of the Royal Society, and by Kendall. Other antecedents discussed include work on dependency by Renyi and Doksum and Samarov, together with the Yule-Simpson paradox. The GMC metric partly extends the concept of Granger causality, so that we consider causality, graphical analy...
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作者：Li, Quefeng; Li, Lexin
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of California System; University of California Berkeley
摘要：Multimodal data, where different types of data are collected from the same subjects, are fast emerging in a large variety of scientific applications. Factor analysis is commonly used in integrative analysis of multimodal data, and is particularly useful to overcome the curse of high dimensionality and high correlations. However, there is little work on statistical inference for factor analysis-based supervised modeling of multimodal data. In this article, we consider an integrative linear regr...
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作者：Schochet, Peter Z.; Pashley, Nicole E.; Miratrix, Luke W.; Kautz, Tim
作者单位：Mathematica; Rutgers University System; Rutgers University New Brunswick; Harvard University
摘要：This article develops design-based ratio estimators for clustered, blocked randomized controlled trials (RCTs), with an application to a federally funded, school-based RCT testing the effects of behavioral health interventions. We consider finite population weighted least-square estimators for average treatment effects (ATEs), allowing for general weighting schemes and covariates. We consider models with block-by-treatment status interactions as well as restricted models with block indicators ...
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作者：Zhang, Jingnan; He, Xin; Wang, Junhui
作者单位：City University of Hong Kong; Shanghai University of Finance & Economics
摘要：Community detection in network data aims at grouping similar nodes sharing certain characteristics together. Most existing methods focus on detecting communities in undirected networks, where similarity between nodes is measured by their node features and whether they are connected. In this article, we propose a novel method to conduct network embedding and community detection simultaneously in a directed network. The network embedding model introduces two sets of vectors to represent the out-...
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作者：Liang, Faming; Xue, Jingnan; Jia, Bochao
作者单位：Purdue University System; Purdue University; Eli Lilly; Lilly Research Laboratories
摘要：This article proposes an innovative method for constructing confidence intervals and assessing p-values in statistical inference for high-dimensional linear models. The proposed method has successfully broken the high-dimensional inference problem into a series of low-dimensional inference problems: For each regression coefficient beta(i), the confidence interval and p-value are computed by regressing on a subset of variables selected according to the conditional independence relations between...
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作者：Li, Yunxiao; Hu, Yi-Juan; Satten, Glen A.
作者单位：Emory University; Centers for Disease Control & Prevention - USA
摘要：Modern statistical analyses often involve testing large numbers of hypotheses. In many situations, these hypotheses may have an underlying tree structure that both helps determine the order that tests should be conducted but also imposes a dependency between tests that must be accounted for. Our motivating example comes from testing the association between a trait of interest and groups of microbes that have been organized into operational taxonomic units (OTUs) or amplicon sequence variants (...
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作者：McCulloch, C. E.; Neuhaus, J. M.
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作者：McShane, Blakeley B.; Bockenholt, Ulf; Hansen, Karsten T.
作者单位：Northwestern University; University of California System; University of California San Diego
摘要：Over the last decade, large-scale replication projects across the biomedical and social sciences have reported relatively low replication rates. In these large-scale replication projects, replication has typically been evaluated based on a single replication study of some original study and dichotomously as successful or failed. However, evaluations of replicability that are based on a single study and are dichotomous are inadequate, and evaluations of replicability should instead be based on ...
