Research Reproducibility as a Survival Analysis

Author/Creator

Author/Creator ORCID

Date

2020-12-17

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Program

Citation of Original Publication

Raff, Edward; Research Reproducibility as a Survival Analysis; Machine Learning (2020); https://arxiv.org/abs/2012.09932

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Abstract

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-ReproducibilitySurvival-Analysis