Preisser John S, Lu Bing, Qaqish Bahjat F
Department of Biostatistics, CB # 7420, School of Public Health, University of North Carolina, Chapel Hill, NC 27599, U.S.A.
Stat Med. 2008 Nov 29;27(27):5764-85. doi: 10.1002/sim.3390.
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.
在二元结局的组内相关性估计方程方法的背景下引入了偏差校正协方差估计量。模拟研究结果表明，在偏差和覆盖概率方面，偏差校正协方差估计量比未校正的三明治估计量表现更好。此外，在估计方程中引入基于矩阵的偏差校正可显著改善组内相关性的点估计和区间估计。使用一项关于减少未成年人饮酒的嵌套横断面整群试验的数据对这些方法进行了说明。
