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作者：Ma, Xinwei; Wang, Jingshen; Wei, Waverly
作者单位：University of California System; University of California San Diego; University of California System; University of California Berkeley; University of Southern California
摘要：Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These designs dynamically adjust treatment allocations during interim analyses based on participant responses and covariates collected during the experiment. However, delayed responses can significantly compromise the effectiveness of CARA designs, as they hinder timely adjustments to treatment assignments when certain partic...
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作者：Zeng, Lang; Tang, Weijing; Ren, Zhao; Ding, Ying
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Carnegie Mellon University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：The stochastic gradient descent (SGD) algorithm has been widely used to optimize deep Cox neural network (Cox-NN) by updating model parameters using mini-batches of data. We show that SGD aims to optimize the average of mini-batch partial-likelihood, which is different from the standard partial-likelihood. This distinction requires developing new statistical properties for the global optimizer, namely, the mini-batch maximum partial-likelihood estimator (mb-MPLE). We establish that mb-MPLE for...
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作者：Zhang, Rongmao; Cheng, Cong; Ke, Yuan; Zhang, Wenyang
作者单位：Zhejiang Gongshang University; University System of Georgia; University of Georgia; University of Macau; University of Macau
摘要：Identifying latent cluster structures in spatial trends constitutes an important yet challenging task in diverse applications. In this article, we propose a novel method based on a discrepancy measure over small spatial blocks that effectively uncovers heterogeneity within dynamic spatial data. Our approach effectively detects boundaries where structural changes occur, thus allowing for more nuanced insights into underlying spatial patterns. Unlike methods predicated on strong stationarity ass...
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作者：Lee, Sze Ming; Chen, Yunxiao; Sit, Tony
作者单位：University of London; London School Economics & Political Science; Chinese University of Hong Kong
摘要：High-dimensional multivariate longitudinal data, which arise when many outcome variables are measured repeatedly over time, are becoming increasingly common in social, behavioral and health sciences. We propose a latent variable model for drawing statistical inferences on covariate effects and predicting future outcomes based on high-dimensional multivariate longitudinal data. This model introduces unobserved factors to account for the between-variable and across-time dependence and assist the...
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作者：Chen, Xuanyu; Zhu, Jin; Zhu, Junxian; Wang, Xueqin; Zhang, Heping
作者单位：Sun Yat Sen University; University of Michigan System; University of Michigan; University of Birmingham; National University of Singapore; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Yale University
摘要：The reconstruction of interaction networks between random events is a critical problem arising from statistical physics and politics, sociology, biology, psychology, and beyond. The Ising model lays the foundation for this reconstruction process, but finding the underlying Ising model from the least amount of observed samples in a computationally efficient manner has been historically challenging for half a century. Using sparsity learning, we present an approach named SLIDE whose sample compl...
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作者：Li, Wei; Liu, Jiapeng; Ding, Peng; Geng, Zhi
作者单位：Renmin University of China; Renmin University of China; University of California System; University of California Berkeley; Beijing Technology & Business University
摘要：Estimating causal effects in a target population with unmeasured confounders is challenging, especially when instrumental variables (IVs) are unavailable. However, IVs from auxiliary populations with similar problems can help infer causal effects in the target population. While the homogeneous conditional average treatment effect assumption has been widely used for effect transportability, it has not been explored in IV-based data fusion. We include it as a basic approach, though it may be bia...
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作者：Ma, Tianwen; Huggins, Jane E.; Kang, Jian
作者单位：Emory University; Rollins School Public Health; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：An Event-Related Potential (ERP)-based Brain-Computer Interface (BCI) Speller System assists people with disabilities to communicate by decoding electroencephalogram (EEG) signals. A P300-ERP embedded in EEG signals arises in response to a rare, but relevant event (target) among a series of irrelevant events (non-target). Different machine learning methods have constructed binary classifiers to detect target events, known as calibration. The existing calibration strategy uses data from partici...
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作者：Zhou, Zheng; Mee, Robert; Hamers, Herbert; Zheng, Wei
作者单位：Beijing University of Technology; University of Tennessee System; University of Tennessee Knoxville; Tilburg University; Tilburg University
摘要：The Shapley value is a well-known concept in cooperative game theory that provides a fair way to distribute revenues or costs among players. It has found applications in many fields besides economics, such as marketing and biology. Recently, it has been widely applied in data science for data quality evaluation and model interpretation. However, the computation of the Shapley value is an NP-hard problem. For a cooperative game with n players, calculating Shapley values for all players requires...
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作者：Cui, Chengyu; Xu, Gongjun
作者单位：University of Michigan System; University of Michigan
摘要：Generalized latent factor analysis not only provides a useful latent embedding approach in statistics and machine learning, but also serves as a widely used tool across various scientific fields, such as psychometrics, econometrics, and social sciences. Ensuring the identifiability of latent factors and the loading matrix is essential for the model's estimability and interpretability, and various identifiability conditions have been employed by practitioners. However, fundamental statistical i...
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作者：Chen, Jiawen; Xiong, Caiwei; Sun, Quan; Song, Yutong; Wang, Geoffery W.; Gupta, Gaorav P.; Halder, Aritra; Li, Yun; Li, Didong
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; Pennsylvania Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Drexel University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Spatial omics technologies revolutionize our view of biological processes within tissues. However, existing methods fail to capture localized, sharp changes characteristic of critical events (e.g., tumor development). Here, we present StarTrail, a novel gradient based method that powerfully defines rapidly changing regions and detects cliff genes, genes exhibiting drastic expression changes at highly localized or disjoint boundaries. StarTrail, the first to leverage spatial gradients for spati...
