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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...
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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...
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作者：Gonzalez-Manteiga, Wenceslao; Dolores Martinez-Miranda, Maria; Van Keilegom, Ingrid
作者单位：Universidade de Santiago de Compostela; University of Granada; Universite Catholique Louvain
摘要：We address the problem of testing for a parametric function of fixed effects in mixed models. We propose a test based on the distance between two empirical error distribution functions, which are constructed from residuals calculated under the opposing hypotheses. The proposed test statistic has power against all alternatives, and its asymptotic distribution is derived. A simulation study shows that the test outperforms others in the literature. The test is applied to longitudinal data from an...
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作者：Efron, Bradley
作者单位：Stanford University
摘要：An unknown prior density g(theta) has yielded realizations Theta(1), ..., Theta(N.) They are unobservable, but each i produces an observable value Xi according to a known probability mechanism, such as Xi similar to Po(Theta(i)). We wish to estimate g(theta) from the observed sample X-1, ..., X-N. Traditional asymptotic calculations are discouraging, indicating very slow nonparametric rates of convergence. In this article we show that parametric exponential family modelling of g(theta) can giv...
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作者：Kong, Shengchun; Nan, Bin
作者单位：Purdue University System; Purdue University; University of Michigan System; University of Michigan
摘要：We consider generalized linear regression with a covariate left-censored at a lower detection limit. Complete-case analysis, where observations with values below the limit are eliminated, yields valid estimates for regression coefficients but loses efficiency, ad hoc substitution methods are biased, and parametric maximum likelihood estimation relies on parametric models for the unobservable tail probability distribution and may suffer from model misspecification. To obtain robust and more eff...
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作者：Simpson, D.; Illian, J. B.; Lindgren, F.; Sorbye, S. H.; Rue, H.
作者单位：University of Bath; University of St Andrews; University of Bath; UiT The Arctic University of Tromso; Norwegian University of Science & Technology (NTNU)
摘要：This paper introduces a new method for performing computational inference on log-Gaussian Cox processes. The likelihood is approximated directly by making use of a continuously specified Gaussian random field. We show that for sufficiently smooth Gaussian random field prior distributions, the approximation can converge with arbitrarily high order, whereas an approximation based on a counting process on a partition of the domain achieves only first-order convergence. The results improve upon th...
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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：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：Ettinger, B.; Perotto, S.; Sangalli, L. M.
作者单位：Emory University; Polytechnic University of Milan
摘要：We propose a regression model for data spatially distributed over general two-dimensional Riemannian manifolds. This is a generalized additive model with a roughness penalty term involving a differential operator computed over the non-planar domain. By virtue of a semiparametric framework, the model allows inclusion of space-varying covariate information. Estimation can be performed by conformally parameterizing the non-planar domain and then generalizing existing models for penalized spatial ...
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作者：Xu, Kelin; Guo, Wensheng; Xiong, Momiao; Zhu, Liping; Jin, Li
作者单位：Fudan University; University of Pennsylvania; University of Texas System; University of Texas Health Science Center Houston; Renmin University of China
摘要：Sufficient dimension reduction has been extensively explored in the context of independent and identically distributed data. In this article we generalize sufficient dimension reduction to longitudinal data and propose an estimating equation approach to estimating the central mean subspace. The proposed method accounts for the covariance structure within each subject and improves estimation efficiency when the covariance structure is correctly specified. Even if the covariance structure is mis...
