Author

Affiliation

Reproduction Researcher Name

University of Exeter

About

This book captures the reproduction of:

[Authors]. [Title]. [Journal] [Volume], [Edition] ([Year]). <[URL]>.

Use the navigation bar above to view:

• Original study - the original study article and associated artefacts.
• Reproduction - code and documentation from reproduction of the model.
• Evaluation - describes model reproduction success and compares original study against guidelines for sharing research, criteria for journal reproducibility guidelines, and article reporting guidelines.
• Logbook - chronological entries detailing reproduction work.
• Summary - summary of the computational reproducibility assessment.

Project team

Conducting this reproduction:

• [Name + Link + ORCID]

Providing support during the reproduction:

• [Name + Link + ORCID]

Other members of the team on STARS:

• Amy Heather
• Thomas Monks
• Alison Harper
• Navonil Mustafee
• Andrew Mayne

Protocol

The protocol for this work is summarised in the diagram below and archived on Zenodo:

Heather, A., Monks, T., Harper, A., Mustafee, N., & Mayne, A. (2024). Protocol for assessing the computational reproducibility of discrete-event simulation models on STARS. Zenodo. https://doi.org/10.5281/zenodo.12179846.

Workflow for computational reproducibility assessment

Citation

APA:

Heather A., Monks T., Harper A., Mustafee N., Mayne A. (2024). Template for computational reproducibility assessments on STARS (version 1.0.4). URL: https://github.com/pythonhealthdatascience/stars_reproduction_template

See CITATION.cff and citation_bibtex.bib for alternative formats.

License

See License page.