Molenaar Dylan, Dolan Conor V
Psychological Methods, Department of Psychology, University of Amsterdam, Weesperplein 4, 1018 XA, Amsterdam, The Netherlands,
Behav Genet. 2014 May;44(3):212-31. doi: 10.1007/s10519-014-9647-9. Epub 2014 Feb 22.
Investigating genotype by environment interactions (GxE) is generally considered challenging due to the scale dependency of the interaction effect. The present paper illustrates the problems associated with testing for GxEs on summed item scores within the well-known ACE model. That is, it is shown how genuine GxEs may be masked and how spurious interactions can arise from scaling issues in the data. A solution is proposed which explicitly distinguishes between a measurement model for the ordinal item responses and a biometric model in which the GxE effects are investigated. The new approach is studied in a simulation study using both a scenario in which the measurement instrument suffers from mild scaling problems and a scenario in which the measurement instrument suffers from severe scaling problems. Results indicate that the severity of the scale problems affects the power to detect GxE, but it rarely results in false positives. We illustrate the new approach on a real dataset concerning affect.
由于交互效应的尺度依赖性，研究基因型与环境的相互作用（GxE）通常被认为具有挑战性。本文阐述了在著名的ACE模型中对总和项目得分进行GxE检验时所涉及的问题。也就是说，展示了真实的GxE如何被掩盖，以及数据中的尺度问题如何导致虚假的相互作用。提出了一种解决方案，该方案明确区分了有序项目反应的测量模型和研究GxE效应的生物统计模型。在一项模拟研究中，使用测量工具存在轻微尺度问题的场景和测量工具存在严重尺度问题的场景，对新方法进行了研究。结果表明，尺度问题的严重程度会影响检测GxE的功效，但很少导致假阳性。我们在一个关于情感的真实数据集上展示了这种新方法。
