Identifying influential families using regression diagnostics for generalized estimating equations

被引:0
|
作者
Ziegler, A
Blettner, M
Kastner, C
Chang-Claude, J
机构
[1] Univ Marburg, Inst Med Biometry & Epidemiol, Med Ctr Methodol & Hlth Res, D-35033 Marburg, Germany
[2] German Canc Res Ctr, Div Epidemiol, D-6900 Heidelberg, Germany
[3] Univ Munich, Inst Stat, Munich, Germany
关键词
correlated data; familial aggregation; marginal model; pseudo maximum likelihood estimation;
D O I
10.1002/(SICI)1098-2272(1998)15:4<341::AID-GEPI2>3.0.CO;2-5
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
The Generalized Estimating Equations (GEE) is an approach to analyze correlated data. It is applied here to data from an epidemiological study of oesophageal cancer in a high incidence area in China to investigate familial aggregation. Regression diagnostics for mean structures and association structures are used to identify families that influence estimates of these structures. It is shown that most of the families influencing the mean structure have a low age of disease onset in common. Most families identified by regression diagnostics for the association structure influence the parent correlation. It is concluded that regression diagnostic techniques can be used to identify clusters influencing mean and association structures of the models. Genet. Epidemiol. 15.341-353, 1998. (C) 1998 Wiley-Liss, Inc.
引用
收藏
页码:341 / 353
页数:13
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