Study designs in public health research often require the estimation of intervention effects that have been applied to a cluster of subjects in a common geographic area, rather than randomly assigned to individual subjects, and where the outcome is dichotomous. Statistical methods that account for t
Analysis of Comparative Data Using Generalized Estimating Equations
β Scribed by EMMANUEL PARADIS; JULIEN CLAUDE
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 192 KB
- Volume
- 218
- Category
- Article
- ISSN
- 0022-5193
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β¦ Synopsis
It is widely acknowledged that the analysis of comparative data from related species should be performed taking into account their phylogenetic relationships. We introduce a new method, based on the use of generalized estimating equations (GEE), for the analysis of comparative data. The principle is to incorporate, in the modelling process, a correlation matrix that specifies the dependence among observations. This matrix is obtained from the phylogenetic tree of the studied species. Using this approach, a variety of distributions (discrete or continuous) can be analysed using a generalized linear modelling framework, phylogenies with multichotomies can be analysed, and there is no need to estimate ancestral character state. A simulation study showed that the proposed approach has good statistical properties with a type-I error rate close to the nominal 5%, and statistical power to detect correlated evolution between two characters which increases with the strength of the correlation. The proposed approach performs well for the analysis of discrete characters. We illustrate our approach with some data on macro-ecological correlates in birds. Some extensions of the use of GEE are discussed.
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