Protocol for assessing the computational reproducibility of discrete-event simulation models on STARS

Reproducible
Authors
Affiliations

Amy Heather

University of Exeter Medical School

Thomas Monks

University of Exeter Medical School

Alison Harper

University of Exeter Business School

Navonil Mustafee

University of Exeter Business School

Andrew Mayne

Somerset NHS Foundation Trust

Published

20 Jun 2024

Doi

10.5281/zenodo.12179845

Summary

This protocol will be used to assess the computational reproducibility of published healthcare discrete-event simulation (DES) models created using Python or R. It forms part of the project STARS: “Sharing Tools and Artefacts for Reproducible Simulations in healthcare”.

Article

Citation

BibTeX citation:
@online{heather2024,
  author = {Heather, Amy and Monks, Thomas and Harper, Alison and
    Mustafee, Navonil and Mayne, Andrew},
  title = {Protocol for Assessing the Computational Reproducibility of
    Discrete-Event Simulation Models on {STARS}},
  date = {2024-06-20},
  url = {https://pythonhealthdatascience.github.io/stars/pages/publications/2024/heather2024protocol/},
  doi = {10.5281/zenodo.12179845},
  langid = {en}
}
For attribution, please cite this work as:
Heather, Amy, Thomas Monks, Alison Harper, Navonil Mustafee, and Andrew Mayne. 2024. “Protocol for Assessing the Computational Reproducibility of Discrete-Event Simulation Models on STARS.” June 20, 2024. https://doi.org/10.5281/zenodo.12179845.