Modeling motivation and affect
Research on affect dynamics and affect regulation (e.g., in job-related contexts) requires intensive data collection methods to allow for the analysis of short-term and longer-term dynamics. These complex data structures typically require hierarchical models with either continuous or discrete latent variables (SEM models or Latent Class models, respectively). The suitability of modeling approaches more typical in cognitive psychology (e.g., MPT models) has not been explored so far. The area "Modeling motivation and affect" therefore includes theses that allow for comparative use of different modeling approaches in this field of research. Moreover, we propose a project that aims at improving statistical techniques for controlling motivational biases in surveys based on innovative MPT models for the randomized response technique. In addition, we propose applications of existing diffusion models, latent state-trait models, and latent-transition models to new research questions on affective counter-regulation and job stressor perceptions.
Possible model development projects
Modeling compliance patterns in intensive longitudinal data (Advisors: Sonnentag, Hilbig, Erdfelder).
Sequential analysis in surveys with randomized response models (Advisors: Ulrich, Erdfelder).
Comparative validation of models for indirect questioning (randomized response) to assess sensitive attributes (Advisors: Hilbig, Erdfelder, Ulrich).
Possible model application projects
Cognitive processes underlying affective counter-regulation (Advisors: Voss, Kiesel).
Exhaustion and perceptions of job stressors: A latent state-trait approach (Advisors: Sonnentag, Lischetzke, Meiser).
The effect of detachment on profiles of affective-motivational experiences (Advisors: Lischetzke, Sonnentag).