This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology

中文翻译：

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从人格特质问卷的有效性和验证性的心理学网络视角

本文回顾了潜在变量和心理测量网络模型对人格特质问卷的验证的因果关系。这些模型暗示了不同的数据生成机制，这些机制对于问卷的有效性和验证具有重要的意义。通过这次审查，我们正式确定了一个从心理学网络角度评估问卷有效性的证据的框架。我们特别关注验证的结构阶段，在该阶段评估项目的冗余性，尺寸和内部结构。在讨论中，我们强调了识别独特个性组成部分的重要性（即，一个或一组共享共同的独特原因的项目），并代表个性网络中每个特征的领域的广度。之后，我们认为心理测量网络模型的度量在统计上等同于因子模型，但我们建议它们的实质性解释有所不同。最后，我们提供了一种新的结构一致性度量，它为内部一致性度量提供了补充信息。对于如何使用心理测量网络模型执行外部验证，我们提供了未来的指导。©2020欧洲人格心理学协会