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作者：Rosenbaum, P. R.
作者单位：University of Pennsylvania
摘要：In an observational study matched for observed covariates, an association between treatment received and outcome exhibited may indicate not an effect caused by the treatment, but merely some bias in the allocation of treatments to individuals within matched pairs. The evidence that distinguishes moderate biases from causal effects is unevenly dispersed among possible comparisons in an observational study: some comparisons are insensitive to larger biases than others. Intuitively, larger treatm...
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作者：Huang, Jing; Ning, Yang; Reid, Nancy; Chen, Yong
作者单位：University of Pennsylvania; Cornell University; University of Toronto
摘要：Composite likelihood functions are often used for inference in applications where the data have a complex structure. While inference based on the composite likelihood can be more robust than inference based on the full likelihood, the inference is not valid if the associated conditional or marginal models are misspecified. In this paper, we propose a general class of specification tests for composite likelihood inference. The test statistics are motivated by the fact that the second Bartlett i...
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作者：Mao, Lu
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：The infinite-dimensional information operator for the nuisance parameter plays a key role in semiparametric inference, as it is closely related to the regular estimability of the target parameter. Calculation of information operators has traditionally proceeded in a case-by-case manner and has often entailed lengthy derivations with complicated arguments. We develop a unified framework for this task by exploiting commonality in the form of semiparametric likelihoods. The general formula develo...
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作者：Sen, Deborshee; Sachs, Matthias; Lu, Jianfeng; Dunson, David B.
作者单位：Duke University; Duke University
摘要：Classification with high-dimensional data is of widespread interest and often involves dealing with imbalanced data. Bayesian classification approaches are hampered by the fact that current Markov chain Monte Carlo algorithms for posterior computation become inefficient as the number of predictors or the number of subjects to classify gets large, because of the increasing computational time per step and worsening mixing rates. One strategy is to employ a gradient-based sampler to improve mixin...
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作者：Lijoi, Antonio; Prunster, Igor; Rigon, Tommaso
作者单位：Bocconi University
摘要：Discrete nonparametric priors play a central role in a variety of Bayesian procedures, most notably when used to model latent features, such as in clustering, mixtures and curve fitting. They are effective and well-developed tools, though their infinite dimensionality is unsuited to some applications. If one restricts to a finite-dimensional simplex, very little is known beyond the traditional Dirichlet multinomial process, which is mainly motivated by conjugacy. This paper introduces an alter...
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作者：Bellach, A.; Kosorok, M. R.; Gilbert, P. B.; Fine, J. P.
作者单位：University of Washington; University of Washington Seattle; University of North Carolina; University of North Carolina Chapel Hill; Fred Hutchinson Cancer Center
摘要：Left-truncation poses extra challenges for the analysis of complex time-to-event data. We propose a general semiparametric regression model for left-truncated and right-censored competing risks data that is based on a novel weighted conditional likelihood function. Targeting the subdistribution hazard, our parameter estimates are directly interpretable with regard to the cumulative incidence function. We compare different weights from recent literature and develop a heuristic interpretation fr...
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作者：Guo, F. Richard; Richardson, Thomas S.
作者单位：University of Washington; University of Washington Seattle
摘要：We consider testing marginal independence versus conditional independence in a trivariate Gaussian setting. The two models are nonnested, and their intersection is a union of two marginal independences. We consider two sequences of such models, one from each type of independence, that are closest to each other in the Kullback-Leibler sense as they approach the intersection. They become indistinguishable if the signal strength, as measured by the product of two correlation parameters, decreases...
