NIH Historical Success Rates Explain Current Attitudes

September 25, 2009

We recently took up the Save-the-New-Investigators defense of the NIH against charges that it is violating the order of primary grant review by untoward administrative shenanigans. I was unhappy with the graphical defense and created a better version. (I see Science repeated the graphical-communication error. They are to be complimented on including the perspective of total funded application numbers though.) NIH-PickupStats-300.png
data source
Whether achieved by close examination or by reformulating the graph, the conclusion should be that the NIH strategy of funding New Investigator out of priority score order only had the effect of equating this number with the number of established investigator grants funded out of order. Note that before 2007 Program were funding about twice as many established-investigator exceptions as new-investigator exceptions. Just sayin’. There is always some context here people. And for those that want to argue that the current support for previously-unfunded scientists is the end of the world and a brand new introduction of age-discrimination….ROFLMAO.
NewINvType1.png
source
I thought we could take the next step and further the examination of NIH funding behavior. In this case the data are the success rates for all competing New applications (termed Type 1) by fiscal year. Calculations of success rates are a bit tricky but basically this shows the number of awarded grants divided by the number submitted for consideration in that fiscal year. So even including the seemingly dramatic increase in out-of-priority-order grant pickups for New Investigators in 2007 (and presumably for 2008), the success rate is still only brought up to the same as established investigators in 2007-2008. A rate which, I will emphasize, is still considerably below that enjoyed by established investigators during the heady years of the NIH doubling (now un-doubled).


If you want to know why those investigators who have not previously held a NIH grant complain about the OldBoyz club and biases against them, well these data are a pretty good place to start. It is harder to get your grant funded if you are a n00b investigator.
RPGsuccessbyYear.png
source
One last graph to explain why the old guard are whining and looking for someone to blame (yeaaaah) about the state of NIH grant funding. I ran across these data in a powerpoint from the NIH (h/t: microfool) and had remarked upon them in an early post. I keep thinking about the data though so I figured I’d just post them. (I had to re-plot it from the embedded chart object to make it readable.) I stick by my original comment. Those who are our older and more established scientists have been shaped by three cycles of NIH budget woes forcing down grant success rates- the early 80s, late 80s into the early 90s (which caused the political pressure leading to the doubling) and the present one starting about 2004 (after the decade-of-the-double). Some of them may have only been trainees for the first one but the campfire lore and attitudes were transmitted. The graph gives us a point of reference. For established investigators in the mid-80s, a success rate of about 37% represented the dismal landing from a down cycle! Then just one cycle later the success rates were down at 25%- OMMFG we have to DO SOMETHING!! The doubling was great and indeed success rates started to go back up towards the 35% value. Which they expected because of their formative experiences. Phew. But then success rates plummeted again, bringing us to our current state of affairs.
You can kind of feel sorry for them. Almost.
Unless you are a New Investigator. Who was up against a much harder fight to get funded all along. So at any given point in time….is just not really going to feel that sorry for whining established investigators.

No Responses Yet to “NIH Historical Success Rates Explain Current Attitudes”


  1. What really makes me sick is this bullshit sensationalism by Science’s shitty “journalist”:

    A new analysis of the grantsmaking process at the National Institutes of Health (NIH) lifts the veil on how many grant proposals are funded even though they fall below a cutoff based on peer-review scores. The bottom line—at least 19% of NIH’s basic research portfolio is funded for reasons that go beyond quality—may stoke simmering concerns about the agency’s policy that favors young investigators.
    [emphasis added]

    Yeah, program is reaching below the payline to pick grants that they know are shit, and are just choosing to fund for the fuck of it. This implication of unsavory “beyond quality” shit is nauseating. As if the study section decision-making process has some kind of lock on assessing “quality”.

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  2. whimple Says:

    Also, the established = tenured investigators can twiddle their thumbs and wait for things to get better. The New Investigators get fired. Just sayin’

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  3. expat posdtoc Says:

    16-18% ain’t so bad. i’ll take 1 in 6 odds any day of the week.

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  4. Cashmoney Says:

    Science and Nature journalists are *journalists* pure and simple. Why would you expect them to get this career stuff right? Or to eschew the sensational for the accurate?

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  5. msphd Says:

    great post! the most clarity I’ve seen on the issue, anywhere.

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  6. jr Says:

    Glad to see that grant funding is starting to catch up to established investigators for what they have created: an unsustainable supply of scientists for the resources available (grants). Maybe now they’ll see that training more and grad students is not really that wise…

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  7. drugmonkey Says:

    Has anyone seen success rate numbers from before the 80s?

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  8. microfool Says:

    You can search the NIH Report Catalog http://report.nih.gov/catalog.aspx by year and find the estimated success rates for R01 equivalents back to 1962:
    http://report.nih.gov/FileLink.aspx?rid=796&ver=1

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  9. drugmonkey Says:

    Thanks!

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  10. […] to a query from a reader off the blog and a resulting request from me, our blog-friend microfool pointed us to some data. Since I don't like Tables, and the figure on […]

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