For more than a decade, it has been known that many common behavior genetics models for a single phenotype can be estimated as multilevel models (e.g., van den Oord 2001; Guo and Wang 2002; McArdle and Prescott 2005; Rabe-Hesketh et al. 2007). This paper extends the current knowledge to (1) multiple phenotypes such that the method is completely general to the variance structure hypothesized, and (2) both higher and lower levels of nesting. The multi-phenotype method also allows extended relationships to be considered (see also, Bard et al. 2012; Hadfield and Nakagawa 2010). The extended relationship model can then be continuously expanded to merge with the case typically seen in the molecular genetics analyses of unrelated individuals (e.g., Yang et al. 2011). We use the multilevel form of behavior genetics models to fit a multivariate three level model that allows for (1) child level variation from unique environments and additive genetics, (2) family level variation from additive genetics and common environments, and (3) neighborhood level variation from broader geographic contexts. Finally, we provide R (R Development Core Team 2020) functions and code for multilevel specification of several common behavior genetics models using OpenMx (Neale et al. 2016).

十多年来，人们已经知道许多单一表型的常见行为遗传学模型可以估计为多级模型（例如，van den Oord 2001；Guo 和 Wang 2002；McArdle 和 Prescott 2005；Rabe-Hesketh 等人。 2007）。本文将当前知识扩展到 (1) 多个表型，使得该方法完全适用于假设的方差结构，以及 (2) 更高和更低级别的嵌套。多表型方法还允许考虑扩展关系（另见 Bard 等人，2012 年；Hadfield 和 Nakagawa，2010 年）。然后可以不断扩展扩展关系模型以与通常在无关个体的分子遗传学分析中看到的案例合并（例如，Yang et al. 2011）。我们使用行为遗传学模型的多级形式来拟合多元三级模型，该模型允许 (1) 来自独特环境和加性遗传学的儿童级变异，(2) 来自加性遗传学和共同环境的家庭级变异，以及 (3) 邻里来自更广泛地理环境的水平变化。最后，我们提供 R（R Development Core Team 2020）函数和代码，用于使用 OpenMx（Neale 等人，2016 年）对几种常见行为遗传学模型进行多级规范。