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In the absence of gold standard for evaluating quality of peer review, considerable attention has been focused on studying reviewer agreement via inter-rater reliability (IRR) which can be thought of as the correlation between scores of different reviewers given to the same grant proposal. Noting that it is not uncommon for IRR in grant peer review studies to be estimated from some range-restricted subset of submissions, we use statistical methods and data analysis of real peer review data to illustrate behavior of such local IRR estimates when only fractions of top-quality proposal submissions are considered. We demonstrate that local IRR estimates are smaller than those obtained from all submissions and that zero local IRR estimates are quite plausible. We note that, from a measurement perspective, when reviewers are asked to differentiate among grant proposals across the whole range of submissions, only IRR measures that correspond to the complete range of submissions are warranted. We recommend against using local IRR estimates in those situations. Moreover, if review scores are intended to be used for differentiating among top proposals, we recommend peer review administrators and researchers to align review procedures with their intended measurement.
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When zero may not be zero: A cautionary note on the use of inter‐rater reliability in evaluating grant peer review
Considerable attention has focused on studying reviewer agreement via inter-rater reliability (IRR) as a way to assess the quality of the peer review process. Inspired by a recent study that reported an IRR of zero in the mock peer review of top-quality grant proposals, we use real data from a complete range of submissions to the National Institutes of Health and to the American Institute of Biological Sciences to bring awareness to two important issues with using IRR for assessing peer review quality. First, we demonstrate that estimating local IRR from subsets of restricted-quality proposals will likely result in zero estimates under many scenarios. In both data sets, we find that zero local IRR estimates are more likely when subsets of top-quality proposals rather than bottom-quality proposals are considered. However, zero estimates from range-restricted data should not be interpreted as indicating arbitrariness in peer review. On the contrary, despite different scoring scales used by the two agencies, when complete ranges of proposals are considered, IRR estimates are above 0.6 which indicates good reviewer agreement. Furthermore, we demonstrate that, with a small number of reviewers per proposal, zero estimates of IRR are possible even when the true value is not zero.
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- Award ID(s):
- 1759825
- PAR ID:
- 10254055
- Date Published:
- Journal Name:
- Journal of the Royal Statistical Society: Series A (Statistics in Society)
- ISSN:
- 0964-1998
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/rssa.12681
