## Abstract A complex web of gene‐gene and gene‐environment interactions likely underlies late‐onset disease development. We compared conditional logistic regression (CLR) and generalized estimating equations (GEE) in modeling such interactions in pedigrees with missing parents. Using the simulatio
Identifying influential families using regression diagnostics for generalized estimating equations
✍ Scribed by Andreas Ziegler; Maria Blettner; Christian Kastner; Jenny Chang-Claude
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 126 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0741-0395
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✦ Synopsis
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.
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