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SSRTcalc: Monte Carlo and Bayesian Stop-Signal Reaction Time Estimation

Estimates stop-signal reaction time (SSRT) in the stop-signal task using the integration and mean methods described by Verbruggen and colleagues (2019) <doi:10.7554/eLife.46323>. In addition to point estimates, the package provides Monte Carlo tools (nonparametric bootstrap confidence intervals, parametric ex-Gaussian simulation, minimum-trial-count and power analysis, and sensitivity analysis under violations of the horse-race assumptions) and Bayesian estimation via 'Stan', including single-subject and hierarchical ex-Gaussian horse-race models with an optional trigger-failure parameter following Matzke and colleagues (2013) <doi:10.1037/a0030543>, posterior inhibition functions, and posterior predictive checks. The Bayesian layer works with either the 'cmdstanr' or 'rstan' backend.

Version: 2.1.1
Depends: R (≥ 4.0.0)
Imports: stats, graphics, grDevices
Suggests: MASS, cmdstanr (≥ 0.5.0), rstan (≥ 2.26.0), posterior, bayesplot, loo, parallel, testthat (≥ 3.0.0)
Published: 2026-07-06
DOI: 10.32614/CRAN.package.SSRTcalc
Author: Anton Leontyev ORCID iD [aut, cre]
Maintainer: Anton Leontyev <antonleontyev at missouristate.edu>
BugReports: https://github.com/agleontyev/SSRTcalc/issues
License: GPL-3
URL: https://github.com/agleontyev/SSRTcalc
NeedsCompilation: no
Additional_repositories: https://mc-stan.org/r-packages/
Materials: README, NEWS
CRAN checks: SSRTcalc results

Documentation:

Reference manual: SSRTcalc.html , SSRTcalc.pdf

Downloads:

Package source: SSRTcalc_2.1.1.tar.gz
Windows binaries: r-devel: SSRTcalc_2.1.1.zip, r-release: SSRTcalc_2.1.1.zip, r-oldrel: SSRTcalc_2.1.1.zip
macOS binaries: r-release (arm64): SSRTcalc_2.1.1.tgz, r-oldrel (arm64): SSRTcalc_2.1.1.tgz, r-release (x86_64): SSRTcalc_2.1.1.tgz, r-oldrel (x86_64): SSRTcalc_2.1.1.tgz
Old sources: SSRTcalc archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SSRTcalc to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.