Authors: Visscher, Peter M.; Benyamin, Beben; White, Ian

Source: Twin Research, Volume 7, Number 6, December 2004 , pp. 670-674(5)

Publisher: Australian Academic Press

Abstract:

It is shown that maximum likelihood estimation of variance components from twin data can be parameterized in the framework of linear mixed models. Standard statistical packages can be used to analyze univariate or multivariate data for simple models such as the ACE and CE models. Furthermore, specialized variance component estimation software that can handle pedigree data and user-defined covariance structures can be used to analyze multivariate data for simple and complex models, including those where dominance and/or QTL effects are fitted. The linear mixed model framework is particularly useful for analyzing multiple traits in extended (twin) families with a large number of random effects.

Document Type: Research article

DOI: http://dx.doi.org/10.1375/1369052042663742

Affiliations: 1: Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Scotland, United Kingdom

Publication date: 2004-12-01

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