-
作者：Hubbard, Alan E.; Van der Laan, Mark J.
作者单位：University of California System; University of California Berkeley
摘要：We propose a new causal parameter, which is a natural extension of existing approaches to causal inference such as marginal structural models. Modelling approaches are proposed for the difference between a treatment-specific counterfactual population distribution and the actual population distribution of an outcome in the target population of interest. Relevant parameters describe the effect of a hypothetical intervention on such a population and therefore we refer to these models as populatio...
-
作者：Cai, Tianxi; Tian, Lu; Solomon, Scott D.; Wei, L. J.
作者单位：Harvard University; Northwestern University; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital
摘要：Under a general regression setting, we propose an optimal unconditional prediction procedure for future responses. The resulting prediction intervals or regions have a desirable average coverage level over a set of covariate vectors of interest. When the working model is not correctly specified, the traditional conditional prediction method is generally invalid. On the other hand, one can empirically calibrate the above unconditional procedure and also obtain its crossvalidated counterpart. Va...
-
作者：Chen, Kani; Ying, Zhiliang; Zhang, Hong; Zhao, Lincheng
作者单位：Hong Kong University of Science & Technology; Columbia University; Chinese Academy of Sciences; University of Science & Technology of China, CAS
摘要：We develop a unified L-1-based analysis-of-variance-type method for testing linear hypotheses. Like the classical L-2-based analysis of variance, the method is coordinate-free in the sense that it is invariant under any linear transformation of the covariates or regression parameters. Moreover, it allows singular design matrices and heterogeneous error terms. A simple approximation using stochastic perturbation is proposed to obtain cut-off values for the resulting test statistics. Both test s...
-
作者：Wermuth, Nanny; Cox, D. R.
作者单位：Chalmers University of Technology; University of Oxford
摘要：Undetected confounding may severely distort the effect of an explanatory variable on a response variable, as defined by a stepwise data-generating process. The best known type of distortion, which we call direct confounding, arises from an unobserved explanatory variable common to a response and its main explanatory variable of interest. It is relevant mainly for observational studies, since it is avoided by successful randomization. By contrast, indirect confounding, which we identify in this...
-
作者：Vanderweele, Tyler J.; Robins, James M.
作者单位：University of Chicago; Harvard University; Harvard T.H. Chan School of Public Health
摘要：Sufficient-component causes are discussed within the deterministic potential outcomes framework so as to formalize notions of sufficient causes, synergism and sufficient cause interactions. Doing so allows for the derivation of counterfactual and empirical conditions for detecting the presence of sufficient cause interactions. The conditions are novel in that, unlike other conditions in the literature, they make no assumption about monotonicity. The conditions can also be generalized and the c...
-
作者：Fraser, D. A. S.; Rousseau, Judith
作者单位：University of Toronto; Universite PSL; Universite Paris-Dauphine
摘要：We have a statistic for assessing an observed data point relative to a statistical model but find that its distribution function depends on the parameter. To obtain the corresponding p-value, we require the minimally modified statistic that is ancillary; this process is called Studentization. We use recent likelihood theory to develop a maximal third-order ancillary; this gives immediately a candidate Studentized statistic. We show that the corresponding p-value is higher-order Un(0, 1), is eq...
-
作者：Bandeen-Roche, Karen; Ning, Jing
作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
摘要：Most research on the study of associations among paired failure times has either assumed time invariance or been based on complex measures or estimators. Little has accommodated competing risks. This paper targets the conditional cause-specific hazard ratio, henceforth called the cause-specific cross ratio, a recent modification of the conditional hazard ratio designed to accommodate competing risks data. Estimation is accomplished by an intuitive, nonparametric method that localizes Kendall's...
-
作者：Rizopoulos, Dimitris; Verbeke, Geert; Molenberghs, Geert
作者单位：Universite Catholique Louvain; Hasselt University
摘要：A common objective in longitudinal studies is the investigation of the association structure between a longitudinal response process and the time to an event of interest. An attractive paradigm for the joint modelling of longitudinal and survival processes is the shared parameter framework, where a set of random effects is assumed to induce their interdependence. In this work, we propose an alternative parameterization for shared parameter models and investigate the effect of misspecifying the...
-
作者：Papaspiliopoulos, Omiros; Roberts, Gareth O.
作者单位：University of Warwick
摘要：Inference for Dirichlet process hierarchical models is typically performed using Markov chain Monte Carlo methods, which can be roughly categorized into marginal and conditional methods. The former integrate out analytically the infinite-dimensional component of the hierarchical model and sample from the marginal distribution of the remaining variables using the Gibbs sampler. Conditional methods impute the Dirichlet process and update it as a component of the Gibbs sampler. Since this require...
-
作者：Kim, Sungduk; Chen, Ming-Hui; Dey, Dipak K.
作者单位：University of Connecticut
摘要：A critical issue in modelling binary response data is the choice of the links. We introduce a new link based on the generalized t-distribution. There are two parameters in the generalized t-link: one parameter purely controls the heaviness of the tails of the link and the second parameter controls the scale of the link. Two major advantages are offered by the generalized t-links. First, a symmetric generalized t-link with an unknown shape parameter is much more identifiable than a Student t-li...
