Raff, Edward2021-05-202021-05-202020-12-17Raff, Edward; Research Reproducibility as a Survival Analysis; Machine Learning (2020); https://arxiv.org/abs/2012.09932http://hdl.handle.net/11603/21578There 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-ReproducibilitySurvival-Analysis13 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.modeling the reproducibility of a papersurvival analysis problemText