Revisiting the Relationship Between Paylines and Success Rates

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Helping connect you with the NIH perspective

s a followup to my recent blog post on fiscal year 2012 success rates, I’d like to post an update of an earlier blog post where I explained how paylines, percentiles and success rates relate to one another. It’s a long one, but should be helpful in understanding what we mean when we look at success rates.

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 “Paylines, Percentiles and Success Rates” with updates added:

I have read or heard much about the dilemma of NIH applicants as they struggle to understand their chances of receiving NIH funding. As budgets flatten and tighten, this discussion has heated up. To declare that NIH success rates have hovered around 20% for the past five years does little to calm the storm of concern when we hear about shrinking percentiles and paylines. So how is it possible to have a success rate of 20% but a payline at the 7^th percentile? Let’s take a few moments to sort out what these things mean and think about how these numbers are derived and how they can differ.

IMPACT SCORE

It all starts with the impact. This score is assigned by reviewers to indicate the scientific and technical merit of an application. Impact scores range between 1 and 9. A score of “1” indicates an exceptionally strong application and “9” indicates an application with substantial weakness. (I always wondered why at NIH low = good and high = bad but that predates me!) In assigning an impact score, reviewers consider each of five scored criteria: significance, investigator, innovation, approach, and environment, along with other factors like protection of human subjects and vertebrate animal care and welfare. Read more about scoring.

more on NIH website