Statistical analysis of correlated data using generalized estimating equations: An orientation

被引:1734
|
作者
Hanley, JA
Negassa, A
Edwardes, MDD
Forrester, JE
机构
[1] McGill Univ, Fac Med, Dept Epidemiol & Biostat, Montreal, PQ H3A 1A2, Canada
[2] Royal Victoria Hosp, Dept Clin Epidemiol, Montreal, PQ H3A 1A1, Canada
[3] Yeshiva Univ, Albert Einstein Coll Med, Dept Epidemiol & Social Med, Div Epidemiol & Biostat, Bronx, NY USA
[4] Tufts Univ, Sch Med, Dept Family Med & Community Hlth, Boston, MA 02111 USA
关键词
correlation; epidemiologic methods; generalized estimating equation; longitudinal studies; odds ratio; statistics;
D O I
10.1093/aje/kwf215
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciate the essence of the method. The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data.
引用
收藏
页码:364 / 375
页数:12
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