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

心理构造，如智力或抑郁，通常是多维的，它们的测量需要足够的内容覆盖。然而，在实践中，一维测量模型通常被采用。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，拟合不一定得到改善）。此外，在具体的科学研究中，一维结构更容易解释。因此，本研究项目旨在进一步发展一维量表的构建方法，这些方法通过局部项目依赖结合潜在的多维性。该方法建立在Edward Ip最近发表的一种方法之上，该方法将多维模型投射到一维模型中。该方法将首先推广到多同义项目的情况。然后，通过仿真研究比较了不同的鲁棒人参数估计方法。由于判别参数定义了多维情况下的构造（与一维情况相比，判别仅决定测量精度），因此将执行和研究不同的旋转。这些轮换将用于确定在统计和内容覆盖方面具有理想属性的判别参数。这些新发展的方法将在人格心理学中得到应用。通过该项目，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，合适的尺度应该抑制足够的内容覆盖。然而，一维模型在研究素质-应力模型和差异易感性假设的背景下提供了优势，特别是在可解释性和复杂性方面。由于易感性通常在基因与环境相互作用的框架内进行研究，因此我们还将包括遗传标记（多态性BDNF Val66Met， DRD2/ANKK1 Taq Ia， 5-HTTLPR和DRD4 VNTR）进行外部验证，以开发合适的规模。

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.