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作者：Guo, Wensheng; You, Mengying; Yi, Jialin; Pontari, Michel A.; Landis, J. Richard
作者单位：University of Pennsylvania; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：By clustering patients with the urologic chronic pelvic pain syndromes (UCPPS) into homogeneous subgroups and associating these subgroups with baseline covariates and other clinical outcomes, we provide opportunities to investigate different potential elements of pathogenesis, which may also guide us in selection of appropriate therapeutic targets. Motivated by the longitudinal urologic symptom data with extensive subject heterogeneity and differential variability of trajectories, we propose a...
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作者：Azriel, David; Brown, Lawrence D.; Sklar, Michael; Berk, Richard; Buja, Andreas; Zhao, Linda
作者单位：Technion Israel Institute of Technology; University of Pennsylvania; Stanford University
摘要：We study a regression problem where for some part of the data we observe both the label variable (Y) and the predictors (X), while for other part of the data only the predictors are given. Such a problem arises, for example, when observations of the label variable are costly and may require a skilled human agent. When the conditional expectation E[Y vertical bar X] is not exactly linear, one can consider the best linear approximation to the conditional expectation, which can be estimated consi...
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作者：Bao, Le; Li, Changcheng; Li, Runze; Yang, Songshan
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Dalian University of Technology; Renmin University of China
摘要：The Population-based HIV Impact Assessment (PHIA) is an ongoing project that conducts nationally representative HIV-focused surveys for measuring national and regional progress toward UNAIDS' 90-90-90 targets, the primary strategy to end the HIV epidemic. We believe the PHIA survey offers a unique opportunity to better understand the key factors that drive the HIV epidemics in the most affected countries in sub-Saharan Africa. In this article, we propose a novel causal structural learning algo...
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作者：Dempsey, Walter; Oselio, Brandon; Hero, Alfred
作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：Network data often arises via a series of structured interactions among a population of constituent elements. E-mail exchanges, for example, have a single sender followed by potentially multiple receivers. Scientific articles, on the other hand, may have multiple subject areas and multiple authors. We introduce a statistical model, termed the Pitman-Yor hierarchical vertex components model (PY-HVCM), that is well suited for structured interaction data. The proposed PY-HVCM effectively models c...
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作者：Bai, Yuehao; Romano, Joseph P.; Shaikh, Azeem M.
作者单位：University of Michigan System; University of Michigan; Stanford University; Stanford University; University of Chicago
摘要：This article studies inference for the average treatment effect in randomized controlled trials where treatment status is determined according to a matched pairs design. By a matched pairs design, we mean that units are sampled iid from the population of interest, paired according to observed, baseline covariates and finally, within each pair, one unit is selected at random for treatment. This type of design is used routinely throughout the sciences, but fundamental questions about its implica...
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作者：Sun, Yan; Song, Qifan; Liang, Faming
作者单位：Purdue University System; Purdue University
摘要：Deep learning has been the engine powering many successes of data science. However, the deep neural network (DNN), as the basic model of deep learning, is often excessively over-parameterized, causing many difficulties in training, prediction and interpretation. We propose a frequentist-like method for learning sparse DNNs and justify its consistency under the Bayesian framework: the proposed method could learn a sparse DNN with at most O(n/ log(n)) connections and nice theoretical guarantees ...
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作者：Goldman, Jacob Vorstrup; Sell, Torben; Singh, Sumeetpal Sidhu
作者单位：University of Cambridge; University of Cambridge
摘要：The use of nondifferentiable priors in Bayesian statistics has become increasingly popular, in particular in Bayesian imaging analysis. Current state-of-the-art methods are approximate in the sense that they replace the posterior with a smooth approximation via Moreau-Yosida envelopes, and apply gradient-based discretized diffusions to sample from the resulting distribution. We characterize the error of the Moreau-Yosida approximation and propose a novel implementation using underdamped Langev...
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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
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作者：Yee, Thomas W.
作者单位：University of Auckland
摘要：The Wald test remains ubiquitous in statistical practice despite shortcomings such as its inaccuracy in small samples and lack of invariance under reparameterization. This article develops on another but lesser-known shortcoming called the Hauck-Donner effect (HDE) whereby a Wald test statistic is no longer monotone increasing as a function of increasing distance between the parameter estimate and the null value. Resulting in an upward biased p-value and loss of power, the aberration can lead ...
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作者：Garcia-Donato, Gonzalo; Paulo, Rui
作者单位：Universidad de Castilla-La Mancha; Universidade de Lisboa; Universidade de Lisboa
摘要：In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, that is, categorical variables. We adopt a model selection perspective, that is, we approach the problem by constructing a class of models, each corresponding to a particular selection of active variables. The methodology is Bayesian and proceeds by computing the posterior probability of each of these models. We highlight the fact that...
