Finite sample adjustments in estimating equations and covariance estimators for intracluster correlations
Statistics in Medicine Published Online: 4 Aug 2008


Bias-corrected covariance estimators are introduced in the context of an estimating equations approach for intracluster correlations among binary outcomes.

Simulation study results show that the bias-corrected covariance estimators perform better than uncorrected sandwich estimators in terms of bias and coverage probabilities. Additionally, introduction of a matrix-based bias-correction into the estimating equations considerably improves point and interval estimation for the intracluster correlations.

The methods are illustrated using data from a nested cross-sectional cluster trial on reducing underage drinking.


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