Compatibility of content coverage and one-dimensional statistical modelling by item response theory models with local item dependencies and an application in personality psychology

心理结构，如智力或抑郁，通常是多维的，其测量需要足够的内容覆盖。然而，在实践中，通常采用一维测量模型。这通常是明智的，因为多维统计方法并不总是提供优势(更高的模型复杂性，适合性不一定会得到改善)。此外，在具体的科学调查中，一维结构更容易解释。因此，本研究项目旨在进一步发展构建一维量表的方法，这些方法通过局部项目依赖来结合潜在的多维性。该方法建立在Edward Ip最近发表的一种方法的基础上，该方法将多维模型投影到一维模型。该方法最初将推广到多切性物品的情况。然后，仿真研究将比较不同的稳健的人参数估计器。由于判别参数定义了多维情况下的构造(与判别仅确定测量精度的一维情况相反)，因此将实施和研究不同的旋转。这些轮换将被用来确定在统计和内容覆盖率方面具有理想特性的区分参数。新开发的方法将应用于人格心理学。通过这个项目，将开发一种易感性的心理测量量表。敏感性(也称为敏感性或脆弱性)是多维的，适当的规模应该会抑制足够的内容覆盖。然而，在素质-压力-模型和差异易感性假设的研究背景下，一维建模提供了优势，特别是在可解释性和复杂性方面。由于易感性通常在基因x环境交互作用的框架内进行研究，我们还将包括遗传标记(BDNF Val66Met、DRD2/ANKK1 Taq Ia、5-HTTLPR和DRD4 VNTR)，用于在制定合适的量表时进行外部验证。

Psychological constructs, such as intelligence or depression, are typically multidimensional and their measurement requires sufficient content coverage. Nevertheless, in practice one-dimensional measurement models are commonly employed. This is often sensible because a multidimensional statistical approach does not always offer advantages (higher model-complexity, fit not necessarily improved). In addition, a one-dimensional construct is easier to interpret in concrete scientific investigations. Hence, this research project aims to further the development of methods for the construction of one-dimensional scales, with these methods incorporating underlying multidimensionality through local item dependence. The approach builds on a recently published method of Edward Ip that projects multidimensional models into unidimensional models. The method will be initially generalized to the case of polytomous items. Then, a simulation study will compare different robust person parameter estimators. Since the discrimination parameters define the construct in the multidimensional case (in contrast to the one-dimensional case where discrimination merely determines measurement accuracy), different rotations will be implemented and investigated. These rotations will be used to identify discrimination parameters with desirable properties in regard to statistics and content coverage. The newly developed methods are to be applied in personality psychology. Through this project, a psychometric scale for susceptibility will be developed. Susceptibility (also named sensitivity or vulnerability) is multi-dimensional and a suitable scale should inhibit sufficient content coverage. Nevertheless, one-dimensional modelling offers advantages within the context of the investigation of the diathesis-stress-model and the differential susceptibility hypothesis, especially with respect to interpretability and complexity. Because susceptibility is often studied in the framework of gene x environment interactions, we will also include genetic markers (the polymorphisms BDNF Val66Met, DRD2/ANKK1 Taq Ia, 5-HTTLPR, and DRD4 VNTR) for external validation in the development of a suitable scale.