FedECA documentation

This package allows to perform both simulations and deployments of federated external control arms (FedECA) analyses.

Before using this code make sure to:

  1. read and accept the terms of the license license.md that can be found at the root of the repository.

  2. read substra’s privacy strategy

  3. read our companion article

  4. activate secure rng in Opacus if you plan on using differential privacy.

Citing this work

@ARTICLE{terrail2023fedeca,
     author = {{Ogier du Terrail}, Jean and {Klopfenstein}, Quentin and {Li}, Honghao and {Mayer}, Imke and {Loiseau}, Nicolas and {Hallal}, Mohammad and {Debouver}, Michael and {Camalon}, Thibault and {Fouqueray}, Thibault and {Arellano Castro}, Jorge and {Yanes}, Zahia and {Dahan}, Laetitia and {Ta{\"\i}eb}, Julien and {Laurent-Puig}, Pierre and {Bachet}, Jean-Baptiste and {Zhao}, Shulin and {Nicolle}, Remy and {Cros}, J{\'e}rome and {Gonzalez}, Daniel and {Carreras-Torres}, Robert and {Garcia Velasco}, Adelaida and {Abdilleh}, Kawther and {Doss}, Sudheer and {Balazard}, F{\'e}lix and {Andreux}, Mathieu},
     title = "{FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings}",
     journal = {arXiv e-prints},
     keywords = {Statistics - Methodology, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning},
     year = 2023,
     month = nov,
     eid = {arXiv:2311.16984},
     pages = {arXiv:2311.16984},
     doi = {10.48550/arXiv.2311.16984},
     archivePrefix = {arXiv},
     eprint = {2311.16984},
     primaryClass = {stat.ME},
     adsurl = {https://ui.adsabs.harvard.edu/abs/2023arXiv231116984O},
     adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

License

FedECA is released under a custom license that can be found under license.md at the root of the repository.

Installation

Getting Started Instructions