Hierarchical Extension of the Lens Model Equation's G Parameter

The G parameter of the lens model equation is a widely used measure of cue-based judgment accuracy, capturing how well individuals align their cue use with ecological validities in probabilistic environments. Despite its popularity across various research domains, the psychological interpretability of G may be severely limited when estimated in the conventional way, that is, based on separate, participant-level regression models. In this project, we identify core statistical limitations of the conventional approach and demonstrate how these may lead to severely biased conclusions about judgment accuracy across a range of plausible scenarios. To remedy these limitations and increase the meaningfulness of G estimates, we propose a novel hierarchical modeling approach.