Biometrical modeling of twin and family data using standard mixed model software
Biometrical modeling of twin and family data using standard mixed model software
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DOI：
10.1111/j.1541-0420.2007.00803.x
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发表时间：
2008-03-01
期刊：
影响因子：
1.9
通讯作者：
Gjessing, H. K.
中科院分区：
文献类型：
--
作者：
Rabe-Hesketh, S.;Skrondal, A.;Gjessing, H. K.
双胞胎或其他家庭数据的生物统计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。方便的参数化，需要很少的随机效应的建议，这使得这样的模型估计使用广泛可用的软件的线性混合模型（连续表型）或广义线性混合模型（分类表型）。我们通过对连续表型出生体重的家庭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。Stata和R/S-PLUS的示例数据集和命令可在Biometrics网站上获得。
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.