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Updated: Feb 23, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Comment on 'Small sample GEE estimation of regression parameters for longitudinal data'
1Department of Economics, Quantitative Methods and Business Strategy, University of Milano-Bicocca, Milan, Italy.
Abstract:
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.
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