= Generalized estimating equation
{title2=$\sum_iD_i^TV_i^{-1}(Y_i-m_i)=0$}
{wiki}
For independent clusters with mean vector $m_i(\theta)$ and positive definite working <covariance matrix> $V_i$, a <generalized estimating equation> solves
$$
\sum_iD_i^TV_i^{-1}(Y_i-m_i)=0,\qquad D_i=\partial m_i/\partial\theta^T.
$$
Correct mean specification and regularity can give a <consistent estimator> of identifiable mean coefficients despite a misspecified working <covariance>. A <sandwich covariance matrix> accounts for actual cluster variation. Mean equations alone cannot identify two parameters that always enter through the same combination.
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