An update on NIH Grant success rates

Apr 15 2010 Published by under NIH Budgets and Economics

The NIH now has an updated (through FY 2009) series of slides and tables depicting several key stats on application submissions and success rates. Venture over the NIH Data Book page to view the carnage. It is nice that they put up the graphs but it can be a little frustrating because they don't seem to put up much in the way of definition of terms. Although it is relatively easy to Google out the definition of "success rate" there are also slides depicting the funding rate.
Two teaser slides for my audience, as always I apologize for my inability to easily process these into readable form but you can go to the original site.
This first one shows the funding rate for grant applications from male and female PIs.

The data stretch across Fiscal Years from 1998 to 2009. I had to go with the funding rate one because it broke it down by Type 1 (new proposals) and Type 2 (competing continuation applications, i.e., for a project which was previously funded). As you can see, women PIs do not enjoy the same funding rate for competing continuation but have been in a dead heat with men on Type 1 applications over the past half decade.


Next we turn to an old favorite, the success rate of PIs who have never been previously funded by the NIH versus those who have. You will recall that we have discussed this topic before and have noted the jump in first timer success from 2006-2007. I will remind you that this only came about because of heavy handed interference of the Program decision making which corrected the considerable bias at the study section level. Anyway, these data show that the combination of NIH initiatives has brought n00b success rates in line with established investigator success rates.


(h/t: Executive Director of the APS)
Success rate:

Success rates are determined by dividing the number of competing applications funded by the sum of the total
number of competing applications reviewed and the number of funded carryovers. Funded carryovers are those applications which were reviewed and not funded in the review year, but were funded in the next year. In the review year, the application is counted only in the success rate denominator (reviewed), but in the next year when the application is funded it is included in the success rate numerator (awarded) and denominator (reviewed).

4 responses so far

  • arrzey says:

    I recognize that these are the population (sensu statistical) and not a sample - that is this is the whole universe of data- and you can't do standard inferential stats. But there are all sorts of cool ways to do resampling on these data to see if the differences are different from chance or not. I suppose I could do this in my copious spare time....

  • pinus says:

    I couldn't seem to locate if they updated the classic age distribution of 1st R01. I wonder if the efforts to increase R01 to new folks has pushed this down a little (or has the trend for longer post-docs countered that change?)

  • msphd says:

    wow. thanks for posting that. I think the one re: women hasn't changed since last time I saw it (status quo = check).
    the other one is kind of mind-boggling, given the furor raised over new measures that were supposed to make it "easier" for new investigators to get funding. I guess it's working perfectly now, if the chances look about equal? And here the old farts were worried it would FAVOR the new investigators unfairly. HAHAHA
    of course I would just LOVE to see these numbers per institute and per study section. I wonder if they have made all of THAT available? 😉 I somehow doubt it but I will check. It would be kind of funny if it turns out that there are some egregiously sexist or ageist study sections and those biases were entirely exposed by this kind of analysis, don't you think?

  • Anonymous says:

    as the graphs show, the highest success rate still is (as has always been ) established males. And it looks like they're not coming close to even being touched by any of the other categories. Some things never change.

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