-
作者：Liao, Jonquil Z.; Cape, Joshua
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
摘要：This paper considers the problem of testing for latent structure in large symmetric data matrices. The goal is to develop statistically principled methodology that is flexible in its applicability, computationally efficient and insensitive to extreme data variation, thereby overcoming limitations of existing approaches. To this end, we introduce and systematically study certain symmetric matrices, called Wilcoxon-Wigner random matrices, whose entries are normalized rank statistics derived from...
-
作者：Lin, K. Z.; Lei, J.
作者单位：University of Washington; University of Washington Seattle; Carnegie Mellon University
摘要：We consider a time-ordered sequence of networks stemming from stochastic block models in which nodes gradually change their membership over time, and no network at any single time-point contains sufficient signal strength to recover its community structure. To estimate the time-varying community structure, we develop the kernel-debiased sum of squares method that performs spectral clustering after a debiased sum-of-squared aggregation of adjacency matrices. Our theory demonstrates, via a novel...
-
作者：Lin, Zeqin; Liu, Yiming; Pan, Guangming; Yao, Chi; Zhou, Jia
作者单位：Nanyang Technological University; Jinan University; Anhui University; Hefei University of Technology
摘要：We consider the problem of identifying the pattern of latent variables in high-dimensional linear latent variable models, which can also be interpreted as determining the source of spiked singular values in the data matrix. Specifically, we test whether the latent variables are continuous or categorical, a distinction that is crucial for data interpretation, but challenging in the high-dimensional regime. To address this inference problem, we analyse the asymptotic behaviour of empirical measu...
-
作者：Casa, A.; Ferrari, D.; Huang, Z.
作者单位：Free University of Bozen-Bolzano; Royal Melbourne Institute of Technology (RMIT)
摘要：Pairwise likelihood is an approximation of the full likelihood function that facilitates the analysis of high-dimensional covariance models. By combining marginal bivariate likelihoods, it effectively simplifies high-dimensional dependencies, making the estimation process more manageable. We introduce estimation of sparse high-dimensional covariance matrices by maximizing a truncated version of the pairwise likelihood function, obtained by including pairwise terms corresponding to nonzero cova...
-
作者：Li, Wei; Duan, Rui; Li, Sai
作者单位：Renmin University of China; Renmin University of China; Harvard University; Tsinghua University
摘要：Learning causal relationships between pairs of complex traits from observational studies is of great interest in many scientific fields. However, most existing methods assume the absence of unmeasured confounding and restrict causal relationships between two traits to be unidirectional, assumptions that may be violated in real-world systems. In this paper, we address the problem of bivariate causal discovery in the presence of unmeasured confounding and potential feedback loops, leveraging pos...
-
作者：Winter, Steven; Melikechi, Omar; Dunson, David B.
作者单位：Duke University
摘要：Gibbs posteriors are proportional to a prior distribution multiplied by an exponentiated loss function, with a key tuning parameter that weights the information in the loss relative to the prior and provides control of posterior uncertainty. Gibbs posteriors provide a principled framework for likelihood-free Bayesian inference; however, in many situations, the inclusion of a single tuning parameter inevitably leads to poor uncertainty quantification. In particular, regardless of the value of t...
-
作者：Lin, Ziming; Han, Fang
作者单位：University of Washington; University of Washington Seattle
摘要：In a landmark paper, Abadie & Imbens (2008)showed that the naive bootstrap is inconsistent when applied to nearest neighbour matching estimators of the average treatment effect with a fixed number of matches. Since then, this finding has inspired numerous efforts to address the inconsistency issue, typically by employing alternative bootstrap methods. In contrast, in this work we show that the naive bootstrap is provably consistent for the original matching estimator, provided that the number ...
-
作者：Moon, Seung Hyun; Park, Byeong U.; Mammen, Enno; Lee, Young Kyung
作者单位：Seoul National University (SNU); Ruprecht Karls University Heidelberg; Kangwon National University
摘要：A new formulation of the additive interaction model is introduced. In contrast to existing approaches, the new formulation separates well the joint effects of covariates that cannot be accounted for by individual main effects. The new approach enables correct interpretation of interaction effects by making them orthogonal to the associated main effects in the $ L<^>{2} $ sense. A new method is developed to estimate the resulting main and interaction effects. Asymptotic $ L<^>{2} $ error rates ...
-
作者：Ren, B.; Ferrari, F.; Fortini, S.; Ventz, S.; Trippa, L.
作者单位：Harvard University; Harvard University Medical Affiliates; McLean Hospital; Merck & Company; Merck & Company USA; Bocconi University; University of Minnesota System; University of Minnesota Twin Cities; Harvard University; Harvard T.H. Chan School of Public Health
摘要：In oncology the efficacy of novel therapeutics often differs across patient subgroups, and these variations are difficult to predict during the initial phases of the drug development process. The relation between the power of randomized clinical trials and heterogeneous treatment effects has been discussed by several authors. In particular, false negative results are likely to occur when the treatment effects concentrate in a subpopulation, but the study design did not account for potential he...
-
作者：Bekerman, William; Dalal, Abhinandan; Del Ninno, Carlo; Small, Dylan S.
作者单位：University of Pennsylvania; The World Bank
摘要：Observational studies are valuable tools for inferring causal effects in the absence of controlled experiments. However, these studies may be biased due to the presence of some relevant, unmeasured set of covariates. One way to mitigate this concern is to identify hypotheses likely to be more resilient to hidden biases by splitting the data into a planning sample for designing the study and an analysis sample for making inferences. We devise a powerful and flexible method for selecting hypothe...
