-
作者：Liang, Hua; Wu, Hulin; Zou, Guohua
作者单位：University of Rochester; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
摘要：The conventional model selection criterion, the Akaike information criterion, AIC, has been applied to choose candidate models in mixed-effects models by the consideration of marginal likelihood. Vaida & Blanchard (2005) demonstrated that such a marginal AIC and its small sample correction are inappropriate when the research focus is on clusters. Correspondingly, these authors suggested the use of conditional AIC. Their conditional AIC is derived under the assumption that the variance-covarian...
-
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：Cook, R. Dennis; Forzani, Liliana
作者单位：University of Minnesota System; University of Minnesota Twin Cities; National University of the Littoral; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
摘要：We introduce covariance reducing models for studying the sample covariance matrices of a random vector observed in different populations. The models are based on reducing the sample covariance matrices to an informational core that is sufficient to characterize the variance heterogeneity among the populations. They possess useful equivariance properties and provide a clear alternative to spectral models for covariance matrices.
-
作者：Lin, Pei-Sheng
作者单位：National Chung Cheng University; National Health Research Institutes - Taiwan
摘要：We use the quasilikelihood concept to propose an estimating equation for spatial data with correlation across the study region in a multi-dimensional space. With appropriate mixing conditions, we develop a central limit theorem for a random field under various L-p metrics. The consistency and asymptotic normality of quasilikelihood estimators can then be derived. We also conduct simulations to evaluate the performance of the proposed estimating equation, and a dataset from East Lansing Woods i...
-
作者：Carroll, Raymond J.; Wang, Yuedong
作者单位：Texas A&M University System; Texas A&M University College Station; University of California System; University of California Santa Barbara
摘要：We investigate the effects of measurement error on the estimation of nonparametric variance functions. We show that either ignoring measurement error or direct application of the simulation extrapolation, SIMEX, method leads to inconsistent estimators. Nevertheless, the direct SIMEX method can reduce bias relative to a naive estimator. We further propose a permutation SIMEX method that leads to consistent estimators in theory. The performance of both the SIMEX methods depends on approximations...
-
作者：Waagepetersen, Rasmus
作者单位：Aalborg University
摘要：The R package spatstat provides a very flexible and useful framework for analysing spatial point patterns. A fundamental feature is a procedure for fitting spatial point process models depending on covariates. However, in practice one often faces incomplete observation of the covariates and this leads to parameter estimation error which is difficult to quantify. In this paper, we introduce a Monte Carlo version of the estimating function used in spatstat for fitting inhomogeneous Poisson proce...
-
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：Li, Guodong; Li, Wai Keung
作者单位：University of Hong Kong
摘要：We consider a unified least absolute deviation estimator for stationary and nonstationary fractionally integrated autoregressive moving average models with conditional heteroscedasticity. Its asymptotic normality is established when the second moments of errors and innovations are finite. Several other alternative estimators are also discussed and are shown to be less efficient and less robust than the proposed approach. A diagnostic tool, consisting of two portmanteau tests, is designed to ch...
-
作者：Chang, Ted; Kott, Phillip S.
作者单位：University of Virginia
摘要：When we estimate the population total for a survey variable or variables, calibration forces the weighted estimates of certain covariates to match known or alternatively estimated population totals called benchmarks. Calibration can be used to correct for sample-survey nonresponse, or for coverage error resulting from frame undercoverage or unit duplication. The quasi-randomization theory supporting its use in nonresponse adjustment treats response as an additional phase of random sampling. Th...
-
作者：Crainiceanu, Ciprian M.; Dominici, Francesca; Parmigiani, Giovanni
作者单位：Johns Hopkins University; Johns Hopkins University
摘要：Often there is substantial uncertainty in the selection of confounders when estimating the association between an exposure and health. We define this type of uncertainty as 'adjustment uncertainty'. We propose a general statistical framework for handling adjustment uncertainty in exposure effect estimation for a large number of confounders, we describe a specific implementation, and we develop associated visualization tools. Theoretical results and simulation studies show that the proposed met...
