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共享和非共享环境因素之间的因果关系方向。

Direction of causation between shared and non-shared environmental factors.

作者信息

Ozaki Koken, Ando Juko

机构信息

Japan Science and Technology Agency, Saitama, Japan.

出版信息

Behav Genet. 2009 May;39(3):321-36. doi: 10.1007/s10519-009-9257-0. Epub 2009 Feb 24.

Abstract

Determining the direction of causation between two related variables is an interesting and challenging problem. A simple regression model is a frequently used statistical tool to find out whether a dependent variable is significantly predicted by an independent variable; however using a simple regression model cannot determine the direction of causation, because the model fit takes no account of this direction. As an approach to this problem, non-normal structural equation modeling (nnSEM; Shimizu and Kano, J Stat Plan Inference 138:3483-3491, 2008) using higher order moments (third, fourth,...) as well as first and second order moments, can be useful. This method enables us to determine the direction of causation using goodness of fit, even for a simple regression model. In this paper, nnSEM is applied to behavior genetics, in particular, to the genetic simplex model. In this context, nnSEM enables us to determine the direction of causation between C (shared environment) factors and between E (non-shared environment) factors. The efficiency of this method is illustrated by simulation studies and the analysis of real longitudinal twin data.

摘要

确定两个相关变量之间的因果关系方向是一个有趣且具有挑战性的问题。简单回归模型是一种常用的统计工具,用于确定自变量是否能显著预测因变量;然而,使用简单回归模型无法确定因果关系的方向,因为模型拟合并未考虑这一方向。作为解决此问题的一种方法,使用高阶矩(第三、第四……)以及一阶和二阶矩的非正态结构方程建模(nnSEM;Shimizu和Kano,《统计规划与推断杂志》138:3483 - 3491,2008)可能会有所帮助。这种方法使我们能够利用拟合优度来确定因果关系的方向,即使对于简单回归模型也是如此。在本文中,nnSEM被应用于行为遗传学,特别是遗传单形模型。在这种情况下,nnSEM使我们能够确定C(共享环境)因素之间以及E(非共享环境)因素之间的因果关系方向。模拟研究和对实际纵向双胞胎数据的分析说明了该方法的有效性。

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