a Department of Psychology , University of Mannheim , Mannheim , Germany.
Multivariate Behav Res. 2018 Sep-Oct;53(5):633-654. doi: 10.1080/00273171.2018.1469966. Epub 2018 May 29.
When measuring psychological traits, one has to consider that respondents often show content-unrelated response behavior in answering questionnaires. To disentangle the target trait and two such response styles, extreme responding and midpoint responding, Böckenholt ( 2012a ) developed an item response model based on a latent processing tree structure. We propose a theoretically motivated extension of this model to also measure acquiescence, the tendency to agree with both regular and reversed items. Substantively, our approach builds on multinomial processing tree (MPT) models that are used in cognitive psychology to disentangle qualitatively distinct processes. Accordingly, the new model for response styles assumes a mixture distribution of affirmative responses, which are either determined by the underlying target trait or by acquiescence. In order to estimate the model parameters, we rely on Bayesian hierarchical estimation of MPT models. In simulations, we show that the model provides unbiased estimates of response styles and the target trait, and we compare the new model and Böckenholt's model in a recovery study. An empirical example from personality psychology is used for illustrative purposes.
在测量心理特征时,人们必须考虑到被调查者在回答问卷时经常表现出与内容无关的反应行为。为了区分目标特征和两种这样的反应模式,极端反应和中点反应,Böckenholt(2012a)基于潜在处理树结构开发了一种项目反应模型。我们提出了对该模型的理论启发式扩展,以测量一致性,即同意常规和反转项目的倾向。从实质上说,我们的方法建立在认知心理学中用于区分定性不同过程的多项式处理树(MPT)模型之上。因此,新的反应模式模型假设肯定反应的混合分布,这些反应要么由潜在的目标特征决定,要么由一致性决定。为了估计模型参数,我们依赖于 MPT 模型的贝叶斯层次估计。在模拟中,我们表明该模型提供了对反应模式和目标特征的无偏估计,并且我们在恢复研究中比较了新模型和 Böckenholt 的模型。人格心理学的一个实证例子用于说明目的。