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July 19, 2010

Archived: More on Criterion Scores

In an earlier post, I presented an analysis of the relationship between the average significance criterion scores provided independently by individual reviewers and the overall impact scores determined at the end of the study section discussion for a sample of 360 NIGMS R01 grant applications reviewed during the October 2009 Council round. Based on the interest in this analysis reflected here and on other blogs, including DrugMonkey and Medical Writing, Editing & Grantsmanship, I want to provide some additional aspects of this analysis. As I noted in the recent post, the criterion score most strongly correlated (0.74) with the overall impact score is approach. Here is a plot showing this correlation:
Plot of approach and overall impact scores in a sample of 360 NIGMS R01 applications reviewed during the October 2009 Council round.
Plot of approach and overall impact scores in a sample of 360 NIGMS R01 applications reviewed during the October 2009 Council round.
Similarly, here is a plot comparing the average innovation criterion score and the overall impact score:
Plot of innovation and overall impact scores in a sample of 360 NIGMS R01 applications reviewed during the October 2009 Council round.
Plot of innovation and overall impact scores in a sample of 360 NIGMS R01 applications reviewed during the October 2009 Council round.
Note that the overall impact score is NOT derived by combining the individual criterion scores. This policy is based on several considerations, including:
  • The effect of the individual criterion scores on the overall impact score is expected to depend on the nature of the project. For example, an application directed toward developing a community resource may not be highly innovative; indeed, a high level of innovation may be undesirable in this context. Nonetheless, such a project may receive a high overall impact score if the approach and significance are strong.
  • The overall impact score is refined over the course of a study section discussion, whereas the individual criterion scores are not.
That being said, it is still possible to derive the average behavior of the study sections involved in reviewing these applications from their scores. The correlation coefficient for the linear combination of individual criterion scores with weighting factors optimized (approximately related to the correlation coefficients between the individual criterion scores and the overall impact factor) is 0.78. The availability of individual criterion scores provides useful data for analyzing study section behavior. In addition, these criterion scores are important parameters that can assist program staff in making funding recommendations.

About the Author

Jeremy Berg

As former NIGMS director, Jeremy oversaw the Institute’s programs to fund biomedical research and to train the next generation of scientists. He was a leader in many NIH-wide activities and also found time to study a variety of molecular recognition processes in his NIH lab.