Analysis of clustered data: A combined estimating equations approach

被引：13

作者：

Stoner, JA ^{[1
]}

Leroux, BG

机构：

[1] Univ Nebraska, Med Ctr, Omaha, NE 68198 USA

[2] Univ Washington, Dept Dent Publ Hlth Sci, Seattle, WA 98195 USA

来源：

BIOMETRIKA | 2002年 / 89卷 / 03期

关键词：

between-cluster and within-cluster effects; generalised estimating equations; optimal estimating equation theory;

D O I：

10.1093/biomet/89.3.567

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Examples of clustered data include data from longitudinal studies and data sampled within groups. This paper proposes a regression analysis method for clustered data that optimally weights and combines contrasts of the data through a combination of estimating equations. Examples of combining between-cluster, within-cluster and longitudinal data contrasts are presented. The method results in increased estimation efficiency relative to generalised estimating equations with standard working correlation structures. The proposed method also simplifies modelling decisions regarding the true correlation structure of the data and avoids correlation parameter estimation.

引用

页码：567 / 578

页数：12

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