Prospect Theory + Drift Diffusion Model + Multi-modal data : Modeling reaction time of risky choice

This project was conducted as the final project for the 2020 Spring Seminar in Experimental Psychology: Computational Modeling at Seoul National University. Here, I conducted the hierarchical Bayesian data analysis on human behaviors of decision making. I implemented models combining the Prospect theory and the Drift Diffusion model to explain reaction time in value-based decision making. Also, I investigated whether incorporating eye-gaze data would yield a better explanation. The models are implemented using the RStan package and fitted in the hierarchical Bayesian framework. There are details at the link.