Journal article
Joint modeling of the association between NIH funding and its three primary outcomes: patents, publications, and citation impact
Scientometrics, v 117(1), pp 591-602
Oct 2018
Abstract
This paper examines the impact of NIH funding on research outcomes using data from 108,803 projects funded by NIH between January 2009 and March 2017. We extend the prior knowledge on this topic by incorporating the correlation structure of multiple research outcomes, as well as a comprehensive list of grant-level features capturing information on funding size, gender composition and funding type. Specifically, we utilize partial least squares regression (PLS) to jointly model all three primary outcomes (publications, patents and citation impact) and identify the effects of grant-level features on research outputs. Our results show that joint modeling of research outcomes via PLS yields a more accurate prediction than analyzing each outcome separately. Additionally, we find that when other grant-level features are held constant, a 2-year-longer project duration would produce a similar improvement in research outputs to that achieved by $1 million in additional funding. Based on this finding, we recommend no-cost extension of funded projects instead of increased funding support to achieve a comparable increase in research outputs. Promoting multi-organizational grants is found to be more effective for increasing patents, whereas encouraging multiple-PI grants is more productive in terms of publications and citation impact. Of the various NIH grant types, program project/center grants (P series) and research training grants (T series) are the two most productive and impactful. Results also suggest that projects with a higher proportion of male PIs tend to produce more research outputs. This finding, however, needs to be interpreted with caution due to the limitation of our data set.
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Details
- Title
- Joint modeling of the association between NIH funding and its three primary outcomes: patents, publications, and citation impact
- Creators
- Fengqing Zhang - 0000 0001 2181 3113 grid.166341.7 Department of Psychology Drexel University Philadelphia PA 19104 USAErjia Yan - 0000 0001 2181 3113 grid.166341.7 College of Computing and Informatics Drexel University Philadelphia PA 19104 USAXin Niu - 0000 0001 2181 3113 grid.166341.7 Department of Psychology Drexel University Philadelphia PA 19104 USAYongjun Zhu - 0000 0001 2181 989X grid.264381.a Department of Library and Information Science Sungkyunkwan University Seoul South Korea
- Publication Details
- Scientometrics, v 117(1), pp 591-602
- Publisher
- Springer International Publishing; Cham
- Grant note
- RE-07-15-0060-15 / Institute of Museum and Library Services (http://dx.doi.org/10.13039/100000208)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology); Information Science
- Web of Science ID
- WOS:000442737700032
- Scopus ID
- 2-s2.0-85050353854
- Other Identifier
- 991014976894404721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science