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Finite sample adjustments in estimating equations and covariance estimators for intracluster correlations
Author(s) -
Preisser John S.,
Lu Bing,
Qaqish Bahjat F.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3390
Subject(s) - estimator , statistics , covariance , context (archaeology) , generalized estimating equation , mathematics , covariance matrix , estimating equations , confidence interval , econometrics , paleontology , biology
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. Copyright © 2008 John Wiley & Sons, Ltd.