This poster presents some tools for utilizing variability in research.
In both society and academic research, there is an increasing emphasis on acknowledging psychological divergences from averages. Yet, techniques required to analyze variability as a subject of interest rather than a nuisance are seldom taught in study programs. Consequently, interested researchers may benefit from support when asking themselves one or more of these questions:
(1) How can I enrich my theories with variability on the conceptual level? (2) How can I use variability to test theories that I otherwise could not distinguish from each other (as with some competing theories of dual-task performance)? (3) How do I test variability hypotheses, especially in the face of measurement error?
To help with this, we created a tutorial and are developing online resources/references.
Drawing from computational cognition research, we propose a theory-oriented workflow that enriches research in experimental/cognitive psychology research with a variability perspective. We take you through five steps from developing a formal theoretical model, to deriving predictions and testing those predictions. Each step’s implementation is illustrated with a fictional researcher’s journey.
Alongside exemplary theoretical mechanisms, we explain how variance function and quantile regression can be used to test hypotheses about variability. The workflow is extensible and easily adapted to specific research contexts. This poster provides an overview over this workflow and its components, providing interested researchers with several potential entry points to this wide class of approaches and perspectives.