-
作者：Zhao, Qingyuan; Small, Dylan S.; Rosenbaum, Paul R.
作者单位：University of Pennsylvania
摘要：We discuss observational studies that test many causal hypotheses, either hypotheses about many outcomes or many treatments. To be credible an observational study that tests many causal hypotheses must demonstrate that its conclusions are neither artifacts of multiple testing nor of small biases from nonrandom treatment assignment. In a sense that needs to be defined carefully, hidden within a sensitivity analysis for nonrandom assignment is an enormous correction for multiple testing: In the ...
-
作者：Backenroth, Daniel; Goldsmith, Jeff; Harran, Michelle D.; Cortes, Juan C.; Krakauer, John W.; Kitago, Tomoko
作者单位：Columbia University; Columbia University; Johns Hopkins University; Johns Hopkins University
摘要：We propose a novel method for estimating population-level and subject-specific effects of covariates on the variability of functional data. We extend the functional principal components analysis framework by modeling the variance of principal component scores as a function of covariates and subject-specific random effects. In a setting where principal components are largely invariant across subjects and covariate values, modeling the variance of these scores provides a flexible and interpretab...
-
作者：Chen, Hao; Chen, Xu; Su, Yi
作者单位：University of California System; University of California Davis; Duke University
摘要：Two-sample tests for multivariate data and non-Euclidean data are widely used in many fields. Parametric tests are mostly restrained to certain types of data that meets the assumptions of the parametric models. In this article, we study a nonparametric testing procedure that uses graphs representing the similarity among observations. It can be applied to any data types as long as an informative similarity measure on the sample space can be defined. The classic test based on a similarity graph ...
-
作者：Ertefaie, Ashkan; Small, Dylan S.; Rosenbaum, Paul R.
作者单位：University of Rochester; University of Pennsylvania
摘要：Weak instruments produce causal inferences that are sensitive to small failures of the assumptions underlying an instrumental variable, so strong instruments are preferred. The possibility of strengthening an instrument at the price of a reduced sample size has been proposed in the statistical literature and used in the medical literature, but there has not been a theoretical study of the trade-off of instrument strength and sample size. This trade-off and related questions are examined using ...
-
作者：Mueller, Jonas; Jaakkola, Tommi; Gifford, David
作者单位：Massachusetts Institute of Technology (MIT)
摘要：We present a nonparametric framework to model a short sequence of probability distributions that vary both due to underlying effects of sequential progression and confounding noise. To distinguish between these two types of variation and estimate the sequential-progression effects, our approach leverages an assumption that these effects follow a persistent trend. This work is motivated by the recent rise of single-cell RNA-sequencing experiments over a brief time course, which aim to identify ...
-
作者：Trapani, Lorenzo
作者单位：City St Georges, University of London
摘要：This article proposes a procedure to estimate the number of common factors k in a static approximate factor model. The building block of the analysis is the fact that the first k eigenvalues of the covariance matrix of the data diverge, while the others stay bounded. On the grounds of this, we propose a test for the null that the ith eigenvalue diverges, using a randomized test statistic based directly on the estimated eigenvalue. The test only requires minimal assumptions on the data, and no ...
-
作者：Murray, Thomas A.; Yuan, Ying; Thall, Peter F.
作者单位：University of Texas System; UTMD Anderson Cancer Center
摘要：Medical therapy often consists of multiple stages, with a treatment chosen by the physician at each stage based on the patient's history of treatments and clinical outcomes. These decisions can be formalized as a dynamic treatment regime. This article describes a new approach for optimizing dynamic treatment regimes, which bridges the gap between Bayesian inference and existing approaches, like Q-learning. The proposed approach fits a series of Bayesian regression models, one for each stage, i...
-
作者：Glynn, Adam N.; Kashin, Konstantin
作者单位：Emory University; Harvard University
摘要：We demonstrate that the front-door adjustment can be a useful alternative to standard covariate adjustments (i.e., back-door adjustments), even when the assumptions required for the front-door approach do not hold. We do this by providing asymptotic bias formulas for the front-door approach that can be compared directly to bias formulas for the back-door approach. In some cases, this allows the tightening of bounds on treatment effects. We also show that under one-sided noncompliance, the fron...
-
作者：Liang, Faming; Li, Qizhai; Zhou, Lei
作者单位：Purdue University System; Purdue University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; State University System of Florida; University of Florida
摘要：Recent advances in high-throughput biotechnologies have provided an unprecedented opportunity for biomarker discovery, which, from a statistical point of view, can be cast as a variable selection problem. This problem is challenging due to the high-dimensional and nonlinear nature of omics data and, in general, it suffers three difficulties: (i) an unknown functional form of the nonlinear system, (ii) variable selection consistency, and (iii) high-demanding computation. To circumvent the first...
-
作者：Fan, Jianqing; Kim, Donggyu
作者单位：Princeton University
摘要：High-frequency financial data allow us to estimate large volatility matrices with relatively short time horizon. Many novel statistical methods have been introduced to address large volatility matrix estimation problems from a high-dimensional Ito process with microstructural noise contamination. Their asymptotic theories require sub-Gaussian or some finite high-order moments assumptions for observed log-returns. These assumptions are at odd with the heavy tail phenomenon that is pandemic in f...
