Analysis of prevention program effectiveness with clustered data using generalized estimating equations.
Analysis of prevention program effectiveness with clustered data using generalized estimating equations.
复制标题
使用广义估计方程通过聚类数据分析预防计划的有效性。
DOI：
10.1037//0022-006x.64.5.919
复制
发表时间：
1996
影响因子：
5.9
通讯作者：
Zarkin,GA
中科院分区：
文献类型：
--
作者：
Norton,EC;Bieler,GS;Ennett,ST;Zarkin,GA
预防计划的实验研究经常随机分组的个人，而不是个人的治疗条件。当在统计分析中没有考虑集群内个体之间的相关性时，标准误差是有偏差的，可能导致关于治疗效果的显著性的误导性结论。本研究演示了广义估计方程（GEE）方法，特别是集中在GEE独立的方法，以控制连续或二进制结果的回归模型中的群内相关性。GEE独立的方法产生一致和稳健的方差估计。数据来自青年药物滥用预防项目DARE。（PsycInfo数据库记录（c）2020阿帕，保留所有权利）
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.(PsycInfo Database Record (c) 2020 APA, all rights reserved)