Project Overview
- Status: Planning
Evaluating Eye-Tracking Consistency and Accuracy and Its Impact on Key Dependent Variables across Different Systems in the ManyBabies2 Project
The goal of this initiative is to examine how variability in eye-tracking data quality across hardware systems, labs, and participants might affect the robustness and interpretability of key dependent measures such as anticipatory looks and differential looking scores. We will use existing eye-tracking data from our first MB2 registered report.
The final data set includes 521 toddlers and 703 adults across 37 labs using a range of eye-tracker systems (Tobii, EyeLink, SMI). This offers a unique opportunity to address crucial methodological questions:
- How do key data quality indicators (e.g., precision, accuracy, temporal delay) vary across eye-tracking systems?
- To what extent and how does variation in eye-tracking data quality influence the robustness and reliability of key dependent variables?
Links
- Listserv: join here
- MB2: main project page
Leads
- Tobias Schuwerk, Ludwig Maximilian University of Munich, Germany [email]
- Shuting Li, Ludwig Maximilian University of Munich, Germany [email]
MB-ManyTrackers Contributors
We encourage everyone who is interested in the project to contact Project Lead Shuting Li. Please note that access to infants/an infant lab is NOT a prerequisite.
Contributor list coming soon