The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
estimate_scr_responsivity_bayes() treats SCR
responsivity as graded evidence rather than a binary preprocessing
deletion rule. It keeps the conventional median-amplitude non-responder
flag, estimates a Beta-Binomial posterior response probability, and
retains every participant with finite trial data for model-based
sensitivity analyses.
This supports a primary-model/robustness workflow in which hard exclusion can be compared with hierarchical retention. The implementation is deliberately transparent and dependency-light; it does not claim to reproduce a Dirichlet-process mixture model.
Methodological motivation includes Thomas & Rabinak (2026), DOI 10.1016/j.biopsycho.2026.109336.
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.