Rabe-Hesketh S, Skrondal A, Gjessing H K
Graduate School of Education & Graduate Group in Biostatistics, University of California, Berkeley, CA 94720, USA.
Biometrics. 2008 Mar;64(1):280-8. doi: 10.1111/j.1541-0420.2007.00803.x. Epub 2007 May 2.
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.
双胞胎或其他家族数据的生物统计学遗传建模可用于将观察到的反应或“表型”的方差分解为遗传和环境成分。本文提出了需要很少随机效应的便捷参数化方法，这使得此类模型能够使用广泛可用的线性混合模型软件（用于连续表型）或广义线性混合模型软件（用于分类表型）进行估计。我们通过对连续表型出生体重的家族数据和二分表型抑郁症的双胞胎数据进行建模来说明所提出的方法。生物统计学网站上提供了示例数据集以及针对Stata和R/S-PLUS的命令。
