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Correlated data are commonly analyzed using models constructed using population-averaged generalized estimating equations (GEEs). The specification of a population-averaged GEE model includes selection of a structure describing the correlation of repeated measures. Accurate specification of this structure can improve efficiency, whereas the finite-sample estimation of nuisance correlation parameters can inflate the variances of regression parameter estimates. Therefore, correlation structure selection criteria should penalize, or account for, correlation parameter estimation. In this article, we compare recently proposed penalties in terms of their impacts on correlation structure selection and regression parameter estimation, and give practical considerations for data analysts. Supplementary materials for this article are available online. 相似文献
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Irga Peter J. Burchett Margaret D. O’Reilly Gabe Torpy Fraser R. 《Urban Ecosystems》2016,19(2):885-898
Urban Ecosystems - Many street trees in urban areas are deciduous and drop leaves during autumn. These leaves are a potential growing substrate for fungi, which when aerosolized and inhaled, can... 相似文献
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