MODELS FOR LONGITUDINAL DATA - A GENERALIZED ESTIMATING EQUATION APPROACH
MODELS FOR LONGITUDINAL DATA - A GENERALIZED ESTIMATING EQUATION APPROACH
复制标题
DOI：
10.2307/2531734
复制
发表时间：
1988-12-01
期刊：
影响因子：
1.9
通讯作者：
ALBERT, PS
中科院分区：
文献类型：
--
作者：
ZEGER, SL;LIANG, KY;ALBERT, PS
本文讨论了用于纵向数据分析的广义线性模型的扩展。考虑两种方法：特定主题（SS）模型，其中回归参数的异质性被明确建模；以及群体平均（PA）模型，其中群体的总体响应是焦点。我们使用广义估计方程方法来拟合离散和连续结果的两类模型。当假设特定于受试者的参数遵循高斯分布时，PA 和 SS 参数之间的简单关系是可用的。通过对母亲吸烟和儿童呼吸道疾病的数据分析来说明这些方法。
This article discusses extensions of generalized linear models for the analysis of longitudinal data. Two approaches are considered: subject-specific (SS) models in which heterogeneity in regression parameters is explicitly modelled: and population-averaged (PA) models in which the aggregate response for the population is the focus. We use a generalized estimating equation approach to fit both classes of models for discrete and continuous outcomes. When the subject-specific parameters are assumed to follow a Gaussian distribution, simple relationships between the PA and SS parameters are available. The methods are illustrated with an anlysis of data on mother''s smoking and children''s respiratory disease.