Research Reproducibility as a Survival Analysis

Authors

  • Edward Raff Booz Allen Hamilton University of Maryland, Baltimore County

Keywords:

Software Engineering

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-Reproducibility-Survival-Analysis

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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. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16124

Issue

Section

AAAI Technical Track on Application Domains