Research Reproducibility as a Survival Analysis
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2020-12-17
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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