-
作者：Hristache, M.; Patilea, V.
作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
摘要：We consider a general statistical model defined by moment restrictions when data are missing at random. Using inverse probability weighting, we show that such a model is equivalent to a model for the observed variables only, augmented by a moment condition defined by the missingness mechanism. Our framework covers parametric and semiparametric mean regressions and quantile regressions. We allow for missing responses, missing covariates and any combination of them. The equivalence result sheds ...
-
作者：Luo, Wei; Zhu, Yeying; Ghosh, Debashis
作者单位：City University of New York (CUNY) System; Baruch College (CUNY); University of Waterloo; Colorado School of Public Health
摘要：In many causal inference problems the parameter of interest is the regression causal effect, defined as the conditional mean difference in the potential outcomes given covariates. In this paper we discuss how sufficient dimension reduction can be used to aid causal inference, and we propose a new estimator of the regression causal effect inspired by minimum average variance estimation. The estimator requires a weaker common support condition than propensity score-based approaches, and can be u...
-
作者：Lee, Kuang-Yao; Li, Bing; Zhao, Hongyu
作者单位：Yale University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional...
-
作者：Ni, Ai; Cai, Jianwen; Zeng, Donglin
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Case-cohort designs are widely used in large cohort studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large, so an efficient variable selection method is necessary. In this paper, we study the properties of a variable selection procedure using the smoothly clipped absolute deviation penalty in a case-cohort design with a diverging number of parameters. We establish the consistency and asymptotic normality of the maximum pena...
-
作者：Chan, Kwun Chuen Gary; Qin, Jing
作者单位：University of Washington; University of Washington Seattle; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：We study nonparametric maximum likelihood estimation for the distribution of spherical radii using samples containing a mixture of one-dimensional, two-dimensional biased and three-dimensional unbiased observations. Since direct maximization of the likelihood function is intractable, we propose an expectation-maximization algorithm for implementing the estimator, which handles an indirect measurement problem and a sampling bias problem separately in the E- and M-steps, and circumvents the need...
-
作者：Miao, Wang; Tchetgen, Eric J. Tchetgen
作者单位：Peking University; Harvard University
摘要：Suppose we are interested in the mean of an outcome variable missing not at random. Suppose however that one has available a fully observed shadow variable, which is associated with the outcome but independent of the missingness process conditional on covariates and the possibly unobserved outcome. Such a variable may be a proxy or a mismeasured version of the outcome and is available for all individuals. We have previously established necessary and sufficient conditions for identification of ...
-
作者：Delaigle, A.; Hall, P.
作者单位：University of Melbourne
摘要：We consider curve extension and linear prediction for functional data observed only on a part of their domain, in the form of fragments. We suggest an approach based on a combination of Markov chains and nonparametric smoothing techniques, which enables us to extend the observed fragments and construct approximated prediction intervals around them, construct mean and covariance function estimators, and derive a linear predictor. The procedure is illustrated on real and simulated data.
-
作者：Lee, Stephen M. S.; Young, G. Alastair
作者单位：University of Hong Kong; Imperial College London
摘要：We consider inference on a scalar parameter of interest in the presence of a nuisance parameter, using a likelihood-based statistic which is asymptotically normally distributed under the null hypothesis. Higher-order expansions are used to compare the repeated sampling distribution, under a general contiguous alternative hypothesis, of p-values calculated from the asymptotic normal approximation to the null sampling distribution of the statistic with the distribution of p-values calculated by ...
-
作者：Sarkar, Sanat K.; Fu, Yiyong; Guo, Wenge
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; New Jersey Institute of Technology
摘要：Seneta & Chen (2005) tightened the familywise error rate control of Holm's procedure by sharpening its critical values using pairwise dependencies of the p-values. In this paper we further sharpen these critical values in the case where the distribution functions of the pairwise maxima of null p-values are convex, a property shown to hold in some applications of Holm's procedure. The newer critical values are uniformly larger, providing tighter familywise error rate control than the approach o...
-
作者：Yang, S.; Kim, J. K.
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Iowa State University
摘要：Multiple imputation is widely used for estimation in situations where there are missing data. Rubin (1987) provided an easily applicable formula for multiple imputation variance estimation, but its validity requires the congeniality condition of Meng (1994), which may not be satisfied for method of moments estimation. We give the asymptotic bias of Rubin's variance estimator when method of moments estimation is used in the complete-sample analysis for each imputed dataset. A new variance estim...
