How is generalized least squares related to within and between estimators in unbalanced panel data?

For a random effects regression model with unbalanced panel data, we demonstrate that the Generalized Least Squares (GLS) estimator can be expressed as a (matrix) weighted average of estimators which utilize the within individual and the between individual variation in the data set. We thus generalize a relationship familiar for balanced panel data. Specific attention must be given to the intercept of the regression. We also define an estimator containing the GLS, the within individual, and the between individual estimators for balanced and unbalanced data as special cases.