ELF: A new measure of response capture

Mathieu Servant, Thibault Gajdos, Karen Davranche

Response capture is a widespread and extensively studied phenomenon, in particular in decision tasks involving response conflict. Its intensity is routinely quantified by conditional accuracy function (CAF). We argue that this method might be misleading, and propose an alternative approach, the error location function (ELF). While CAF provides the error rate by bins of reaction time (RT), ELF represents the share of total errors below each quantile of RT. We derive from ELF an index of response capture, the error location index (ELI), which represents the area below the ELF. Using simulations of computational models, we show that ELF and ELI specifically quantify variations in response capture. Finally, we illustrate the usefulness of ELF and ELI through experimental data and show that ELF and CAF can yield to contradictory conclusions.