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作者：Toulis, Panos
作者单位：University of Chicago
摘要：Randomization tests rely on simple data transformations and possess an appealing robustness property. In addition to being finite-sample valid if the data distribution is invariant under the transformation, these tests can be asymptotically valid under a suitable studentization of the test statistic, even if the invariance does not hold. However, practical implementation often encounters noisy data, resulting in approximate randomization tests that may not be as robust. In this paper, one key ...
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作者：Grainger, J. P.; Rajala, T. A.; Murrell, D. J.; Olhede, S. C.
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Natural Resources Institute Finland (Luke); University of London; University College London
摘要：Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes and randomly sampled spatial processes. Joint analysis of such collections of observations is clearly desirable, but complicated by the lack of an easily implementable analysis framework. We fill this gap by providing a multitaper analysis framework using coupled discrete and continuous data tapers, combined with the discrete Fourier transform for inference. Using ...
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作者：Zhang, Yao; Zhao, Qingyuan
作者单位：National University of Singapore; University of Cambridge
摘要：Sensitivity analysis for the unconfoundedness assumption is crucial in observational studies. For this purpose, the marginal sensitivity model has gained popularity in recent years owing to its good interpretability and mathematical properties. However, most existing models only consider a worst-case parameter that bounds the logit difference between the observed-data and full-data propensity scores, which may not fully capture the extent of unmeasured confounding. We propose a new sensitivity...
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作者：Toulis, Panos
作者单位：University of Chicago
摘要：Randomization tests rely on simple data transformations and possess an appealing robustness property. In addition to being finite-sample valid if the data distribution is invariant under the transformation, these tests can be asymptotically valid under a suitable studentization of the test statistic, even if the invariance does not hold. However, practical implementation often encounters noisy data, resulting in approximate randomization tests that may not be as robust. In this paper, one key ...
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作者：Grainger, J. P.; Rajala, T. A.; Murrell, D. J.; Olhede, S. C.
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Natural Resources Institute Finland (Luke); University of London; University College London
摘要：Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes and randomly sampled spatial processes. Joint analysis of such collections of observations is clearly desirable, but complicated by the lack of an easily implementable analysis framework. We fill this gap by providing a multitaper analysis framework using coupled discrete and continuous data tapers, combined with the discrete Fourier transform for inference. Using ...
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作者：Zhang, Yao; Zhao, Qingyuan
作者单位：National University of Singapore; University of Cambridge
摘要：Sensitivity analysis for the unconfoundedness assumption is crucial in observational studies. For this purpose, the marginal sensitivity model has gained popularity in recent years owing to its good interpretability and mathematical properties. However, most existing models only consider a worst-case parameter that bounds the logit difference between the observed-data and full-data propensity scores, which may not fully capture the extent of unmeasured confounding. We propose a new sensitivity...
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作者：Clausen, David S.; Teichman, Sarah, V; Willis, Amy D.
作者单位：University of Washington; University of Washington Seattle
摘要：We consider the problem of estimating ratios of means of a multivariate outcome across covariates when the data are observed with unknown sample-specific and category-specific perturbations. Our model admits a partially identifiable estimand, and we establish full identifiability by imposing interpretable parameter constraints. To reduce bias and guarantee the existence of estimators in the presence of sparse observations, we apply an asymptotically negligible and constraint-invariant penalty ...
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作者：Dunson, David B.; Wu, Nan
作者单位：Duke University; University of Texas System; University of Texas Dallas
摘要：It is often of interest to infer lower-dimensional structure underlying complex data. As a flexible class of nonlinear structures, it is common to focus on Riemannian manifolds. Most existing manifold-learning algorithms replace the original data with lower-dimensional coordinates without providing an estimate of the manifold or using it to denoise the original data. This article proposes a new methodology to address these issues, allowing interpolation of the estimated manifold between the fi...
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作者：Lee, Yonghoon; Dobriban, Edgar; Tchetgen Tchetgen, Eric J.
作者单位：University of Pennsylvania
摘要：We consider the problem of comparing a reference distribution with several other distributions. Given a sample from both the reference and the comparison groups, we aim to identify the comparison groups whose distributions differ from that of the reference group. Viewing this as a multiple-testing problem, we introduce a methodology that provides exact, distribution-free control of the false discovery rate. To do so, we introduce the concept of batch conformal p -values and demonstrate that th...
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作者：Martin, A.; Santacatterina, M.; Diaz, I
作者单位：New York University
摘要：Marginal structural models are a popular method for estimating causal effects in the presence of time-varying exposures. In spite of their popularity, no scalable nonparametric estimator exists for marginal structural models with multi-valued or continuous time-varying treatments. In this paper, we combine flexible, data-adaptive regression methods, including ensemble learning techniques, with recent developments in semiparametric efficiency theory for longitudinal studies to propose such an e...
