Lunardon N, Scharfstein D
Department of Economics, Quantitative Methods and Business Strategy, University of Milano-Bicocca, Milan, Italy.
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, U.S.A.
Stat Med. 2017 Sep 30;36(22):3596-3600. doi: 10.1002/sim.7366.
In longitudinal studies, the generalized estimating equation (GEE) estimator of the parameters of a marginal model is known to be consistent even if the working intra-subject covariance matrix is incorrectly specified. Recently, a small sample correction for the bias of the GEE estimator has been proposed. We show that this correction formula relies on the correct specification of the working intra-subject covariance matrix. We provide a revised formula that is valid under misspecification and develop the R package 'BCgee' to ease the practical use of the formula. Copyright © 2017 John Wiley & Sons, Ltd.
在纵向研究中,即使工作的受试者内协方差矩阵指定错误,边际模型参数的广义估计方程(GEE)估计量也是一致的。最近,有人提出了一种针对GEE估计量偏差的小样本校正方法。我们表明,这种校正公式依赖于工作的受试者内协方差矩阵的正确指定。我们提供了一个在错误指定情况下有效的修正公式,并开发了R包“BCgee”以方便该公式的实际应用。版权所有© 2017约翰·威利父子有限公司。