Skip to main content
eScholarship
Open Access Publications from the University of California

Biometrical modeling of twin and family data using standard mixed model software.

  • Author(s): Rabe-Hesketh, S
  • Skrondal, A
  • Gjessing, HK
  • et al.

Published Web Location

http://www.gllamm.org/BIOMtwins_08.pdf
No data is associated with this publication.
Creative Commons 'BY-NC-ND' version 4.0 license
Abstract

Biometrical genetic modeling of twin or other family data can be used to decompose the variance of an observed response or 'phenotype' into genetic and environmental components. Convenient parameterizations requiring few random effects are proposed, which allow such models to be estimated using widely available software for linear mixed models (continuous phenotypes) or generalized linear mixed models (categorical phenotypes). We illustrate the proposed approach by modeling family data on the continuous phenotype birth weight and twin data on the dichotomous phenotype depression. The example data sets and commands for Stata and R/S-PLUS are available at the Biometrics website.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Item not freely available? Link broken?
Report a problem accessing this item