New York University School of Medicine
Office of Sponsored Programs Administration

Paylines and Percentile Scoring

The NIH ranks new applications and then determines a cut-off point which they will use to decide which range of numerical ranks of applications will be funded and which will not.

The paylines and policies concerning them vary by institute.

The ranking of applications takes place when an application receives its' initial peer review.

Factors which an NIH institute consider when setting annual paylines include:

• Congressional mandates affecting budgets.
• The Institute tries to balance the payments for existing grants and congressional mandates with the goal of funding as many new worthy applications as possible.
• Appropriations for the current fiscal year.
• The Institutes needs to be able to meet payments for existing grants with project start dates before the current fiscal year.
• The number of applications clustered at each percentile.
• Average grant costs.

Review groups assign priority scores for applications from 1.0 to 5.0 with 1.0 considered outstanding and 5.0 considered acceptable. On the summary statement, the numbers are converted to read between 100 and 500. These numbers are averaged and then calculated into Percentiles. Percentiles range from .5 to 99.5, and lower numbers represent higher scores. The chart below illustrates how paylines are calculated:

Paylines are usually set by institutions by type of application. One example of this is the NIAID's payline for R01 applications for FY03 at 22.0 percentile. This means that R01 applications with a 22.0 or lower score were funded. This represented a funding success rate of 38% of R01 applications received by the NIAID in FY03.

Other Institutes and other funding mechanisms offered by the NIAID may use the priority score as described above to help determine paylines instead of using percentiles.

One of the drawbacks of using the priority score instead of the percentile is that the applications' rankings may become highly clustered.

One of the drawbacks of using the percentile score instead of a priority score is that the wider redistribution which occurs when percentiles are used will distort the percentiles if the priority scores are heavily clustered, which they often are.