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作者：Zhang, Yao; Zhao, Qingyuan
作者单位：Stanford University; University of Cambridge
摘要：The meaning of randomization tests has become obscure in statistics education and practice over the last century. This article makes a fresh attempt at rectifying this core concept of statistics. A new term-quasi-randomization test-is introduced to define significance tests based on theoretical models and distinguish these tests from the randomization tests based on the physical act of randomization. The practical importance of this distinction is illustrated through a real stepped-wedge clust...
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作者：Laga, Ian; Bao, Le; Niu, Xiaoyue
作者单位：Montana State University System; Montana State University Bozeman; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Aggregated Relational Data (ARD), formed from How many X's do you know? questions, is a powerful tool for learning important network characteristics with incomplete network data. Compared to traditional survey methods, ARD is attractive as it does not require a sample from the target population and does not ask respondents to self-reveal their own status. This is helpful for studying hard-to-reach populations like female sex workers who may be hesitant to reveal their status. From December 20...
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作者：Xia, Fan; Chan, Kwun Chuen Gary
作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
摘要：Natural mediation effects are often of interest when the goal is to understand a causal mechanism. However, most existing methods and their identification assumptions preclude treatment-induced confounders often present in practice. To address this fundamental limitation, we provide a set of assumptions that identify the natural direct effect in the presence of treatment-induced confounders. Even when some of those assumptions are violated, the estimand still has an interventional direct effec...
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作者：Gabriel, Erin E.; Sjolander, Arvid; Sachs, Michael C.
作者单位：Karolinska Institutet
摘要：Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments, making the intervention effect that the experiment was designed to estimate nonidentifiable. Nonparametric causal bounds provide a way to narrow the range of possible values for a nonidentifiable causal effect with minimal assumptions. We derive novel bounds for the causal risk difference for a binary outcome and intervention in randomized experiments with nonignorable missingness that is caused ...
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作者：Ke, Zheng Tracy; Ma, Yucong; Lin, Xihong
作者单位：Harvard University; Harvard University; Harvard T.H. Chan School of Public Health
摘要：The spiked covariance model has gained increasing popularity in high-dimensional data analysis. A fundamental problem is determination of the number of spiked eigenvalues, K. For estimation of K, most attention has focused on the use of top eigenvalues of sample covariance matrix, and there is little investigation into proper ways of using bulk eigenvalues to estimate K. We propose a principled approach to incorporating bulk eigenvalues in the estimation of K. Our method imposes a working mode...
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作者：Xu, Tianchen; Chen, Yuan; Zeng, Donglin; Wang, Yuanjia
作者单位：Columbia University; Memorial Sloan Kettering Cancer Center; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Digital technologies (e.g., mobile phones) can be used to obtain objective, frequent, and real-world digital phenotypes from individuals. However, modeling these data poses substantial challenges since observational data are subject to confounding and various sources of variabilities. For example, signals on patients' underlying health status and treatment effects are mixed with variation due to the living environment and measurement noises. The digital phenotype data thus shows extensive vari...
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作者：Zhou, Yu; Wang, Lan; Song, Rui; Zhao, Tuoyi
作者单位：University of Miami; North Carolina State University
摘要：In many important applications of precision medicine, the outcome of interest is time to an event (e.g., death, relapse of disease) and the primary goal is to identify the optimal individualized decision rule (IDR) to prolong survival time. Existing work in this area have been mostly focused on estimating the optimal IDR to maximize the restricted mean survival time in the population. We propose a new robust framework for estimating an optimal static or dynamic IDR with time-to-event outcomes ...
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作者：Qi, Zhengling; Pang, Jong-Shi; Liu, Yufeng
作者单位：George Washington University; University of Southern California; University of North Carolina; University of North Carolina Chapel Hill
摘要：With the emergence of precision medicine, estimating optimal individualized decision rules (IDRs) has attracted tremendous attention in many scientific areas. Most existing literature has focused on finding optimal IDRs that can maximize the expected outcome for each individual. Motivated by complex individualized decision making procedures and the popular conditional value at risk (CVaR) measure, we propose a new robust criterion to estimate optimal IDRs in order to control the average lower ...
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作者：Dai, Xiongtao; Lopez-Pintado, Sara
作者单位：Iowa State University; Northeastern University
摘要：We develop a novel exploratory tool for non-Euclidean object data based on data depth, extending celebrated Tukey's depth for Euclidean data. The proposed metric halfspace depth, applicable to data objects in a general metric space, assigns to data points depth values that characterize the centrality of these points with respect to the distribution and provides an interpretable center-outward ranking. Desirable theoretical properties that generalize standard depth properties postulated for Euc...
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作者：Tendijck, Stan; Eastoe, Emma; Tawn, Jonathan; Randell, David; Jonathan, Philip
作者单位：Lancaster University; Royal Dutch Shell; Royal Dutch Shell
摘要：There currently exist a variety of statistical methods for modeling bivariate extremes. However, when the dependence between variables is driven by more than one latent process, these methods are likely to fail to give reliable inferences. We consider situations in which the observed dependence at extreme levels is a mixture of a possibly unknown number of much simpler bivariate distributions. For such structures, we demonstrate the limitations of existing methods and propose two new methods: ...
