The data and analysis underlying NIH’s decision to cap research support lacked rigor and transparency: a commentary
- Published
- Accepted
- Subject Areas
- Science Policy
- Keywords
- science policy, NIH, Grant Support Index, Relative Citation Ratio, productivity, returns on investment, rigor, transparency, funding
- Copyright
- © 2017 Janssens et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. The data and analysis underlying NIH’s decision to cap research support lacked rigor and transparency: a commentary. PeerJ Preprints 5:e3106v1 https://doi.org/10.7287/peerj.preprints.3106v1
Abstract
The US National Institutes of Health (NIH) recently announced that they would limit the number of grants per scientist and redistribute their funds across a larger group of researchers. The policy was withdrawn a month later after criticism from the scientific community. Even so, the basis of this defunct policy was flawed and it merits further examination. The amount of grant support would have been quantified using a new metric, the Grant Support Index (GSI), and limited to a maximum of 21 points, the equivalent of three R01 grants. This threshold was decided based upon analysis of a new metric of scientific output, the annual weighted Relative Citation Ratio, which showed a pattern of diminishing returns at higher values of the GSI. In this commentary, we discuss several concerns about the validity of the two metrics and the quality of the data that the NIH had used to set the grant threshold. These concerns would have warranted a re-analysis of new data to confirm the legitimacy of the GSI threshold. Data-driven policies that affect the careers of scientists should be justified by nothing less than a rigorous analysis of high-quality data.
Author Comment
This is a preprint submission to PeerJ Preprints.