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作者：Berzuini, Carlo; Dawid, A. Philip
作者单位：University of Manchester; University of Cambridge
摘要：We define mechanistic interaction between the effects of two variables on an outcome in terms of departure of these effects from a generalized noisy-OR model in a stratum of the population. We develop a fully probabilistic framework for the observational identification of this type of interaction via excess risk or superadditivity, one novel feature of which is its applicability when the interacting variables have been generated by arbitrarily dichotomizing continuous exposures. The method all...
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作者：Oguz-Alper, M.; Berger, Y. G.
作者单位：Statistics Norway; University of Southampton
摘要：Survey data are often collected with unequal probabilities from a stratified population. In many modelling situations, the parameter of interest is a subset of a set of parameters, with the others treated as nuisance parameters. We show that in this situation the empirical likelihood ratio statistic follows a chi-squared distribution asymptotically, under stratified single and multi-stage unequal probability sampling, with negligible sampling fractions. Simulation studies show that the empiric...
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作者：Kong, Dehan; Xue, Kaijie; Yao, Fang; Zhang, Hao H.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Toronto; University of Arizona
摘要：In modern experiments, functional and nonfunctional data are often encountered simultaneously when observations are sampled from random processes and high-dimensional scalar covariates. It is difficult to apply existing methods for model selection and estimation. We propose a new class of partially functional linear models to characterize the regression between a scalar response and covariates of both functional and scalar types. The new approach provides a unified and flexible framework that ...
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作者：Hennig, C.; Viroli, C.
作者单位：University of London; University College London; University of Bologna
摘要：Classification with small samples of high-dimensional data is important in many application areas. Quantile classifiers are distance-based classifiers that require a single parameter, regardless of the dimension, and classify observations according to a sum of weighted componentwise distances of the components of an observation to the within-class quantiles. An optimal percentage for the quantiles can be chosen by minimizing the misclassification error in the training sample. It is shown that ...
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作者：Augugliaro, Luigi; Mineo, Angelo M.; Wit, Ernst C.
作者单位：University of Palermo; University of Groningen
摘要：We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important properties that distinguish it from the group lasso. First, its solution curve is based on the invariance properties of a generalized linear model. Second, it adds groups of variables based on a gr...
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作者：Su, Z.; Zhu, G.; Chen, X.; Yang, Y.
作者单位：State University System of Florida; University of Florida; National University of Singapore; McGill University
摘要：The envelope model allows efficient estimation in multivariate linear regression. In this paper, we propose the sparse envelope model, which is motivated by applications where some response variables are invariant with respect to changes of the predictors and have zero regression coefficients. The envelope estimator is consistent but not sparse, and in many situations it is important to identify the response variables for which the regression coefficients are zero. The sparse envelope model pe...
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作者：Han, Peisong
作者单位：University of Waterloo
摘要：Intrinsic efficiency and multiple robustness are desirable properties in missing data analysis. We establish both for estimating the mean of a response at the end of a longitudinal study with drop-out. The idea is to calibrate the estimated missingness probability at each visit using data from past visits. We consider one working model for the missingness probability and multiple working models for the data distribution. Intrinsic efficiency guarantees that, when the missingness probability is...
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作者：Liu, L.; Hudgens, M. G.; Becker-Dreps, S.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：We consider inference about the causal effect of a treatment or exposure in the presence of interference, i.e., when one individual's treatment affects the outcome of another individual. In the observational setting where the treatment assignment mechanism is not known, inverse probability-weighted estimators have been proposed when individuals can be partitioned into groups such that there is no interference between individuals in different groups. Unfortunately this assumption, which is some...
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作者：Rosenbaum, P. R.
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作者：Fang, Fang; Shao, Jun
作者单位：East China Normal University
摘要：Existing methods for handling nonignorable missing data rely on the correct specification of parametric models, which is difficult to check. By utilizing the information carried in an instrument, we propose a novel model selection criterion, called the penalized validation criterion, in the presence of nonignorable nonresponse with unspecified propensity. The proposed method can consistently select the most compact correct parametric model from a group of candidate models if one of the candida...
