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.

译文

在测量心理特征时,必须考虑到受访者在回答问卷时经常表现出与内容无关的反应行为。为了解开目标特征和极端响应和中点响应这两种响应方式,b ö ckenholt (2012a) 开发了基于潜在处理树结构的项目响应模型。我们建议对该模型进行理论上的扩展,以衡量默认情况,即与常规项目和反向项目一致的趋势。实质上,我们的方法建立在多项处理树 (MPT) 模型的基础上,该模型在认知心理学中用于区分定性不同的过程。因此,新的响应样式模型假定肯定响应的混合分布,这由潜在的目标特征或默许决定。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响应样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b ö ckenholt的模型。出于说明目的,使用了来自人格心理学的经验示例。

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