-
作者：Jentsch, Carsten; Kirch, Claudia
作者单位：University of Mannheim; Otto von Guericke University
摘要：This article is motivated by several articles that propose statistical inference where the independence of wavelet coefficients for both short- as well as long-range dependent time series is assumed. We focus on the sample variance and investigate the influence of the dependence between wavelet coefficients and this statistic. To this end, we derive asymptotic distributional properties of the sample variance for a time series that is synthesized, ignoring some or all dependence between wavelet...
-
作者：Liu, Wei; Zhang, Zhiwei; Schroeder, R. Jason; Ho, Martin; Zhang, Bo; Long, Cynthia; Zhang, Hui; Irony, Telba Z.
作者单位：US Food & Drug Administration (FDA)
摘要：In some therapeutic areas, treatment evaluation is frequently complicated by a possible placebo effect (i.e., the psychobiological effect of a patient's knowledge or belief of being treated). When a substantial placebo effect is likely to exist, it is important to distinguish the treatment and placebo effects in quantifying the clinical benefit of a new treatment. These causal effects can be formally defined in a joint causal model that includes treatment (e.g., new vs. placebo) and treatmenta...
-
作者：Kang, Hyunseung; Zhang, Anru; Cai, T. Tony; Small, Dylan S.
作者单位：University of Pennsylvania; University of Pennsylvania
摘要：Instrumental variables have been widely used for estimating the causal effect between exposure and outcome. Conventional estimation methods require complete knowledge about all the instruments' validity; a valid instrument must not have a direct effect on the outcome and not be related to unmeasured confounders. Often, this is impractical as highlighted by Mendelian randomization studies where genetic markers are used as instruments and complete knowledge about instruments' validity is equival...
-
作者：Gaskins, J. T.; Daniels, M. J.; Marcus, B. H.
作者单位：University of Louisville; University of Texas System; University of Texas Austin; University of California System; University of California San Diego
摘要：Inference on data with missingness can be challenging, particularly if the knowledge that a measurement was unobserved provides information about its distribution. Our work is motivated by the Commit to Quit II study, a smoking cessation trial that measured smoking status and weight change as weekly outcomes. It is expected that dropout in this study was informative and that patients with missed measurements are more likely to be smoking, even after conditioning on their observed smoking and w...
-
作者：Blocker, Alexander W.; Airoldi, Edoardo M.
作者单位：Harvard University
摘要：We consider the problem of estimating the genome-wide distribution of nucleosome positions from paired end sequencing data. We develop a modeling approach based on nonparametric templates to control for the variability along the sequence of read counts associated with nucleosomal DNA due to enzymatic digestion and other sample preparation steps, and we develop a calibrated Bayesian method to detect local concentrations of nucleosome positions. We also introduce a set of estimands that provides...
-
作者：Yu, Zhou; Dong, Yuexiao; Zhu, Li-Xing
作者单位：Beijing Normal University; Hong Kong Baptist University
摘要：We propose trace pursuit for model-free variable selection under the sufficient dimension-reduction paradigm. Two distinct algorithms are proposed: stepwise trace pursuit and forward trace pursuit. Stepwise trace pursuit achieves selection consistency with fixed p. Forward trace pursuit can serve as an initial screening step to speed up the computation in the case of ultrahigh dimensionality. The screening, consistency property of forward trace pursuit based on sliced inverse regression is est...
-
作者：Ding, Peng; Dasgupta, Tirthankar
作者单位：Harvard University
摘要：Causal inference in completely randomized treatment-control studies with binary outcomes is discussed from Fisherian, Neymanian, and Bayesian perspectives, using the potential outcomes model. A randomization-based justification of Fisher's exact test is provided. Arguing that the crucial assumption of constant causal effect is often unrealistic, and holds only for extreme cases, some new asymptotic and Bayesian inferential procedures are proposed. The proposed procedures exploit the intrinsic ...
-
作者：Taddy, Matt
作者单位：Microsoft; University of Chicago
-
作者：Louis, Thomas A.; Keiding, Niels
作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; University of Copenhagen
-
作者：Jing, Bing-Yi; Li, Zhouping; Pan, Guangming; Zhou, Wang
作者单位：Hong Kong University of Science & Technology; Lanzhou University; Nanyang Technological University; National University of Singapore
摘要：The article is concerned with empirical Bayes shrinkage estimators for the heteroscedastic hierarchical normal model using Stein's unbiased estimate of risk (SURE). Recently, Xie, Kou, and Brown proposed. a class of estimators for this type of problems and established their asymptotic optimality properties under the assumption of known but unequal variances. In this article, we consider this problem with unequal and unknown variances, which may be more appropriate in real situations. By placin...
