Detecting Differential Item Functioning in Multidimensional Graded Response Models With Recursive Partitioning

Differential item functioning (DIF) is a common challenge when examining latent traits in large scale surveys. In recent work, methods from the field of machine learning such as model-based recursive partitioning have been proposed to identify subgroups with DIF when little theoretical guidance and many potential subgroups are available. On this basis, we propose and compare recursive partitioning techniques for detecting DIF with a focus on measurement models with multiple latent variables and ordinal response data. We implement tree-based approaches for identifying subgroups that contribute to DIF in multidimensional latent variable modeling and propose a robust, yet scalable extension, inspired by random forests. The proposed techniques are applied and compared with simulations. We show that the proposed methods are able to efficiently detect DIF and allow to extract decision rules that lead to subgroups with well fitting models.

Neurocognitive Effects of Self-Determined Choice and Emotional Arousal on Time Estimation

Even though effects of emotion and motivation on cognition are well documented, the interaction of all three factors is rarely investigated. Here, we used electroencephalography (EEG) to examine the effects of self-determined choice-as an experimental manipulation of intrinsic motivation - and emotional stimulus content on task preparation and engagement in a temporal production task. Behavioral results indicated a modulation of time processing depending on choice and emotional content. Underlying EEG signals revealed differential modulations by choice on the contingent negative variation (CNV) during task and response preparation and by emotional content on the late positive potential (LPP) in response to the onset of an emotional picture during temporal production. Also, we obtained preliminary evidence for interaction effects of choice and emotional content on the LPP. The feedback-related negativity (FRN) in response to information regarding temporal production success was also affected by interactions of choice and emotional content. These findings indicate that besides separate effects of motivation and emotion, there may be time windows during task engagement in which both factors jointly affect cognitive processing. These results are interpreted as dynamic modulations of attentional resource allocation.