Seitz Timo, Alagöz Ö Emre C, Meiser Thorsten
University of Mannheim, Mannheim, Germany.
Educ Psychol Meas. 2025 Jul 29:00131644251341843. doi: 10.1177/00131644251341843.
High-stakes personality assessments are often compromised by faking, where test-takers distort their responses according to social desirability. Many previous models have accounted for faking by modeling an additional latent dimension that quantifies each test-taker's degree of faking. Such models assume a homogeneous response strategy among all test-takers, reflected in a measurement model in which substantive traits and faking jointly influence item responses. However, such a model will be misspecified if, for some test-takers, item responding is only a function of substantive traits or only a function of faking. To address this limitation, we propose a mixture modeling extension of the multidimensional nominal response model (M-MNRM) that can be used to account for qualitatively different response strategies and to model relationships of strategy use with external variables. In a simulation study, the M-MNRM exhibited good parameter recovery and high classification accuracy across multiple conditions. Analyses of three empirical high-stakes datasets provided evidence for the consistent presence of the specified latent classes in different personnel selection contexts, emphasizing the importance of accounting for such kind of response behavior heterogeneity in high-stakes assessment data. We end the article with a discussion of the model's utility for psychological measurement.
高风险人格评估常常因应试者根据社会期望歪曲回答而受到影响。许多先前的模型通过构建一个额外的潜在维度来量化每个应试者的伪装程度，以此来考虑伪装因素。这些模型假定所有应试者的反应策略是一致的，这在一个测量模型中有所体现，即实质性特质和伪装共同影响项目反应。然而，如果对于某些应试者而言，项目反应仅是实质性特质的函数或者仅是伪装的函数，那么这样的模型就会被错误设定。为解决这一局限性，我们提出了多维名义反应模型（M-MNRM）的混合建模扩展，它可用于解释质上不同的反应策略，并对策略使用与外部变量之间的关系进行建模。在一项模拟研究中，M-MNRM在多种条件下都表现出良好的参数恢复能力和较高的分类准确率。对三个实证高风险数据集的分析为在不同人员选拔背景下一致存在特定潜在类别提供了证据，强调了在高风险评估数据中考虑这种反应行为异质性的重要性。我们在文章结尾讨论了该模型在心理测量中的效用。
