Norton E C, Bieler G S, Ennett S T, Zarkin G A
Center for Economics Research, Research Triangle Institute, North Carolina, USA.
J Consult Clin Psychol. 1996 Oct;64(5):919-26. doi: 10.1037//0022-006x.64.5.919.
Experimental studies of prevention programs often randomize clusters of individuals rather than individuals to treatment conditions. When the correlation among individuals within clusters is not accounted for in statistical analysis, the standard errors are biased, potentially resulting in misleading conclusions about the significance of treatment effects. This study demonstrates the generalized estimating equations (GEE) method, focusing specifically on the GEE-independent method, to control for within-cluster correlation in regression models with either continuous or binary outcomes. The GEE-independent method yields consistent and robust variance estimates. Data from project DARE, a youth substance abuse prevention program, are used for illustration.
预防项目的实验研究通常将个体群组随机分配到不同的治疗条件中，而非将个体随机分配。当在统计分析中未考虑群组内个体之间的相关性时，标准误差会产生偏差，这可能会导致关于治疗效果显著性的误导性结论。本研究展示了广义估计方程（GEE）方法，特别关注独立于GEE的方法，以控制具有连续或二元结果的回归模型中的组内相关性。独立于GEE的方法可产生一致且稳健的方差估计。来自青少年药物滥用预防项目DARE的数据用于说明。
