Research Reproducibility as a Survival Analysis
DOI:
https://doi.org/10.1609/aaai.v35i1.16124Keywords:
Software EngineeringAbstract
There has been increasing concern within the machine learning community that we are in a reproducibility crisis. As many have begun to work on this problem, all work we are aware of treat the issue of reproducibility as an intrinsic binary property: a paper is or is not reproducible. Instead, we consider modeling the reproducibility of a paper as a survival analysis problem. We argue that this perspective represents a more accurate model of the underlying meta-science question of reproducible research, and we show how a survival analysis allows us to draw new insights that better explain prior longitudinal data. The data and code can be found at https://github.com/EdwardRaff/Research-Reproducibility-Survival-AnalysisDownloads
Published
2021-05-18
How to Cite
Raff, E. (2021). Research Reproducibility as a Survival Analysis. Proceedings of the AAAI Conference on Artificial Intelligence, 35(1), 469-478. https://doi.org/10.1609/aaai.v35i1.16124
Issue
Section
AAAI Technical Track on Application Domains