Fitting Procedures for Novel Gene-by-Measured Environment Interaction Models in Behavior Genetic Designs.
Fitting Procedures for Novel Gene-by-Measured Environment Interaction Models in Behavior Genetic Designs.
复制标题
行为遗传设计中新的基因测量环境相互作用模型的拟合程序。
DOI：
10.1007/s10519-015-9707-9
复制
发表时间：
2015
影响因子：
2.6
通讯作者：
Rathouz,PaulJ
中科院分区：
文献类型：
--
作者：
Zheng,Hao;Rathouz,PaulJ
对于定量行为遗传学（例如，双胞胎）研究，珀塞尔提出了一种新的模型来测试基因与测量环境（GxM）的相互作用，同时考虑基因与环境的相关性。Rathouz等人将该模型扩展为更广泛的一类非线性生物计量模型，用于量化和测试这种相互作用。在这项工作中，我们提出了一种新的分解这类模型的可能性，并采用数值积分技术来实现模型估计，特别是对于那些没有封闭形式的可能性。我们的程序的有效性，建立通过数值模拟研究。新的程序说明了一个双胞胎研究分析的调节作用，出生体重对儿童焦虑的遗传影响。第二个例子在在线附录中给出。现存的GXM模型和新的非线性模型都严格假设所有结构成分的正态性，这意味着连续的，但不是正态的，明显的反应变量。
For quantitative behavior genetic (e.g., twin) studies, Purcell proposed a novel model for testing gene-by-measured environment (GxM) interactions while accounting for gene-by-environment correlation. Rathouz et al. expanded this model into a broader class of non-linear biometric models for quantifying and testing such interactions. In this work, we propose a novel factorization of the likelihood for this class of models, and adopt numerical integration techniques to achieve model estimation, especially for those without close-form likelihood. The validity of our procedures is established through numerical simulation studies. The new procedures are illustrated in a twin study analysis of the moderating effect of birth weight on the genetic influences on childhood anxiety. A second example is given in an online appendix. Both the extant GxM models and the new non-linear models critically assume normality of all structural components, which implies continuous, but not normal, manifest response variables.