In my previous post, I presented (among other things) the distribution of the percentage of A0 applications within the pool of funded R01 grants across institutions. This distribution showed that, among the top 100 institutions in terms of total NIH funding in fiscal year 2013, some institutions showed notably higher fractions of A0 applications among their funded R01 grants. Based on this and other analyses, this suggested that this supports the notion that these institutions enjoy higher success rates for their R01 applications. This surrogate may be useful since NIH does not release success rates by institution.
Before I present further analyses of these data, I need to note some technical issues. The data present in the NIH RePORTER data base can be challenging with regard to longitudinal analysis across institutions. While the data are relatively clean with regard the use of institutional names within a given year, they are less clean moving from one year to the next for many institutions. Institutional names can vary through the use of different abbreviations, punctuation, and so one. For example, the University of Michigan is listed as UNIVERSITY OF MICHIGAN AT ANN ARBOR for 2001-2006 and UNIVERSITY OF MICHIGAN for 2007-2014. This required construction of a data set with these ambiguities removed as much as possible. In addition, in my first analysis I determined the percentage of funded A0 applications among R01 grants for each year and then averaged these values. A more robust approach is to determine the total number of funded A0 applications for all years and then divide this value by the total number of R01 grants over the same period. I will use this method for all subsequent analyses.
In considering why some institutions show a higher percentage of A0 applications among their funded R01 grants, one important fact to keep in mind is that the success rates for competing renewal (Type 2) applications are generally higher (typically by approximately a factor of 2) than those for new (Type 1) applications. For example, in FY2013, the overall R01 success rate across NIH was 17%. This breaks down as a success rate of 14% for new (Type 1) applications and 31% for competing renewal (Type 2) applications. This observation suggests two possible explanations for the higher overall percentage of A0 applications among R01 grants at some institutions. First, the percentage of competing renewal (Type 2) grants among the funded R01s might be larger for some institutions than for others and this might account for the higher percentage of A0 applications overall in the grant pool. Second, the percentage of A0 applications among R01 grants might be higher even for new (Type 1) applications for these institutions. Of course, these explanations are not mutually exclusive. They are essentially independent and may or may not be correlated by virtue of institutional characteristics.
The distribution of funded Type 2 applications among funded R01 grants across institutions are shown below:
The institutions with the higher fraction of Type 2 applications are:
|1||MASSACHUSETTS INSTITUTE OF TECHNOLOGY|
|2||JOSLIN DIABETES CENTER|
|5||UNIVERSITY OF CALIFORNIA BERKELEY|
|7||INDIANA UNIVERSITY BLOOMINGTON|
|8||UNIVERSITY OF OREGON|
|10||STATE UNIVERSITY NEW YORK STONY BROOK|
|12||HARVARD UNIVERSITY (MEDICAL SCHOOL)|
|13||UNIVERSITY OF CALIFORNIA SANTA CRUZ|
|15||SCRIPPS RESEARCH INSTITUTE|
|16||TUFTS UNIVERSITY BOSTON|
|17||NEW YORK UNIVERSITY|
|18||COLORADO STATE UNIVERSITY|
|19||UNIVERSITY OF WISCONSIN-MADISON|
|20||OREGON HEALTH & SCIENCE UNIVERSITY|
|21||UNIVERSITY OF COLORADO|
|22||PENNSYLVANIA STATE UNIVERSITY|
|23||UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN|
|24||CALIFORNIA INSTITUTE OF TECHNOLOGY|
At the other end of the distribution, institutions with relatively low fractions of Type 2 applications in their funded R01 pools include a number of major clinical centers including Seattle Children's Hospital (0.167), Cincinnati Children's Hospital (0.225), M.D. Anderson Cancer Center (0.268), Massachusetts General Hospital (0.285), and Brigham and Women's Hospital (0.297). This may reflect the lower rate of submission of Type 2 applications for clinical (as opposed to basic science) studies noted in an NIH publication from 2008.
The distribution of the percentage of A0 applications within the pool of R01 grants across institutions is shown below:
The institutions with the higher percentages of A0 applications among their funded R01 grants are:
|3||CALIFORNIA INSTITUTE OF TECHNOLOGY|
|4||UNIVERSITY OF CALIFORNIA SANTA CRUZ|
|5||SALK INSTITUTE FOR BIOLOGICAL STUDIES|
|6||J. DAVID GLADSTONE INSTITUTES|
|7||MASSACHUSETTS INSTITUTE OF TECHNOLOGY|
|8||COLD SPRING HARBOR LABORATORY|
|11||UNIVERSITY OF CALIFORNIA BERKELEY|
|12||MOREHOUSE SCHOOL OF MEDICINE|
|13||FRED HUTCHINSON CAN RES CTR|
|14||DANA-FARBER CANCER INST|
|15||CHILDREN'S HOSPITAL CORPORATION|
|16||COLUMBIA UNIV NEW YORK MORNINGSIDE|
|17||UNIVERSITY OF COLORADO|
|18||INDIANA UNIVERSITY BLOOMINGTON|
|20||HARVARD UNIVERSITY (MEDICAL SCHOOL)|
|21||RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK|
|22||OREGON HEALTH & SCIENCE UNIVERSITY|
|23||UNIVERSITY OF CHICAGO|
|24||CINCINNATI CHILDRENS HOSP MED CTR|
Note that 10 institutions appear on both lists. Indeed, these two parameters are substantially correlated as shown below:
The correlation coefficient between these two parameters is approximately 0.4. These data reveal that both factors contribute to the increased percentage of A0 applications among funded R01 grants at some institutions.
These analyses provide some data that may help sort out the factors that contribute to the higher percentage of funded A0 applications among R01 grants at some institutions, including those factors that contribute to the success of applications such as the reputations and seniority of the applicants, institutional biases in peer review, and other factors. I welcome comments about how these analyses might be extended.