Finite sample adjustments in estimating equations and covariance estimators for intracluster correlations.
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.
Preisser
John S
JS
Department of Biostatistics, CB # 7420, School of Public Health, University of North Carolina, Chapel Hill, NC 27599, U.S.A. jpreisse@bios.unc.edu
Lu
Bing
B
Qaqish
Bahjat F
BF
D000293:Adolescent; D000294:Adolescent Behavior; D000367:Age Factors; D000428:Alcohol Drinking / Q000453:epidemiology / Q000331:legislation & jurisprudence / Q000517:prevention & control*; D000704:Analysis of Variance; D015982:Bias; D002986:Clinical Trials as Topic; D016000:Cluster Analysis; D016001:Confidence Intervals; D005500:Follow-Up Studies; D006801:Humans; D007604:Juvenile Delinquency; D008297:Male; D015233:Models, Statistical; D013997:Time Factors; D014481:United States; D055815:Young Adult