He just keeps that data crack flowing for the grant geeks in the audience. Today's analysis breaks down the NIGMS funded and unfunded applications by Investigator status. Early Stage Investigator and New Investigator (collectively never had a major R01 award before, distinguished by ESI's having to be no more than 10 yrs out from terminal degree) applications are identified as are Type 1 (new submissions) and Type 2 (competing continuation applications for established investigators.
A plot of the overall impact score versus the percentile for 655 NIGMS R01 applications reviewed during the January 2010 Council round. Solid symbols show applications for which awards have been made and open symbols show applications for which awards have not been made. Red circles indicate early stage investigators, blue squares indicate new investigators who are not early stage investigators and black diamonds indicate established investigators.
Yowsa, data galore!
Go over to his post, he has a cumulative percentile breakdown that is pretty fascinating too.
Director Berg is once again to be congratulated for really leading the way at the NIH. Transparency of this type cannot help but accrue to the benefit of Institutes that are making funding decisions in a reasonable way. Sure, there are going to be cases to explain such as the poor sucker with the fantastic score that didn't get funded. But these data point to the relative consistency with which their apparent exceptional funding decisions (aka "pickups") are made. These types of plots (especially the cumulative one he included but I've not poached here) also help us to assess the degree to which study sections are disadvantaging ESI or NI apps in their scoring and how so. Are the truly excellent top 10% getting their due but then things break down in the grey zone? Are study sections assigning good ESI/PI apps to the scored but decidedly not-good ranges of 25-35th%ile land? Do these relationships change over time as the NIH commitment to ESI/NI investigators takes hold?