Response times in economic games
Can you predict whether someone will repeat their action or switch based on their response times in a similar situation?
Collaborators: Ian Krajbich
Programming: CSS, HTML, Javascript, R, stan
Skills: Bayesian Statistics, Clustering, Experiment, Linear and Logistic Mixed Effects Regressions, Model Comparison, Model Simulation and Model Fitting, Sequential Sampling Models
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Can you predict whether someone will repeat their action or switch based on their response times in a similar situation?
A robust finding in the individual decision-making literature is the link between response times (RT) and strength of preference; decision times are longest when the utilities of the two options are close to each other. This relationship is a feature of sequential sampling models, such as the Drift Diffusion Model (DDM) (you can read more about it here). Extending this understanding to interactive decision-making settings, we explore the applicability of this RT-preference relationship across four extensively studied game types in game theory: stag-hunt (SH), hawk-dove (HD), prisoner’s dilemma (PD), and harmony (HG) games.
Our findings reveal that subjects’ choices not only conform to expected utility but also exhibit sensitivity to the difference in expected utility, as reflected in their RTs. Through model comparison, we demonstrate that the DDM outperforms a non-DDM model that treats choices and RTs as independent. Consequently, RTs serve as a valuable metric for inferring individuals’ likelihood of repeating their previous actions.