University Of Tasmania
Download file
Download file
Download file
3 files

A Bayesian approach for estimating the probability of trigger failures in the stop-signal paradigm

journal contribution
posted on 2023-05-18, 15:03 authored by Matzke, D, Love, J, Heathcote, A
Response inhibition is frequently investigated using the stop-signal paradigm, where participants perform a two-choice response time task that is occasionally interrupted by a stop signal instructing them to withhold their response. Stop-signal performance is formalized as a race between a go and a stop process. If the go process wins, the response is executed; if the stop process wins, the response is inhibited. Successful inhibition requires fast stop responses and a high probability of triggering the stop process. Existing methods allow for the estimation of the latency of the stop response, but are unable to identify deficiencies in triggering the stop process. We introduce a Bayesian model that addresses this limitation and enables researchers to simultaneously estimate the probability of trigger failures and the entire distribution of stopping latencies. We demonstrate that trigger failures are clearly present in two previous studies, and that ignoring them distorts estimates of stopping latencies. The parameter estimation routine is implemented in the BEESTS software (Matzke et al., Front. Quantitative Psych. Measurement, 4, 918; 2013a) and is available at


Publication title

Behavior Research Methods








Tasmanian School of Medicine


Springer New York LLC

Place of publication

United States

Rights statement

© The Author(s) 2016. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

Repository Status

  • Open

Socio-economic Objectives

Expanding knowledge in psychology