Murray Aja Louise, Molenaar Dylan, Johnson Wendy, Krueger Robert F
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
Department of Psychology, University of Edinburgh, Edinburgh, UK.
Behav Genet. 2016 Jul;46(4):552-72. doi: 10.1007/s10519-016-9783-5. Epub 2016 Feb 1.
Estimates of gene-environment interactions (GxE) in behavior genetic models depend on how a phenotype is scaled. Inappropriately scaled phenotypes result in biased estimates of GxE and can sometimes even suggest GxE in the direction opposite to its true direction. Previously proposed solutions are mathematically complex, computationally demanding and may prove impractical for the substantive researcher. We, therefore, evaluated two simple-to-use alternatives: (1) straightforward non-linear transformation of sum scores and (2) factor scores from an appropriate item response theory (IRT) model. Within Purcell's (2002) GxM framework, both alternatives provided less biased parameter estimates, and improved false and true positive rates than using a raw sum score. These approaches are, therefore, recommended over using raw sum scores in tests of GxE. Circumstances under which IRT factor scores versus transformed sum scores should be preferred are discussed.
行为遗传模型中基因-环境相互作用(GxE)的估计取决于表型的缩放方式。表型缩放不当会导致GxE估计出现偏差,有时甚至会在与真实方向相反的方向上提示GxE。先前提出的解决方案在数学上很复杂,计算要求很高,对于实证研究人员来说可能不切实际。因此,我们评估了两种易于使用的替代方法:(1)对总和分数进行直接的非线性变换,以及(2)来自适当项目反应理论(IRT)模型的因子分数。在珀塞尔(2002)的GxM框架内,与使用原始总和分数相比,这两种替代方法都提供了偏差较小的参数估计,并提高了假阳性率和真阳性率。因此,在GxE检验中,推荐使用这些方法而非原始总和分数。文中还讨论了应优先选择IRT因子分数而非变换后的总和分数的情况。