September 8, 2016
In previous blogs, we talked about citation measures as one metric for scientific productivity. Raw citation counts are inherently problematic – different fields cite at different rates, and citation counts rise and fall in the months to years after a publication appears. Therefore, a number of bibliometric scholars have focused on developing methods that measure citation impact while also accounting for field of study and time of publication. We are pleased to report that on September 6, PLoS Biology published a paper from our NIH colleagues in the Office of Portfolio Analysis on “The Relative Citation Ratio: A New Metric that Uses Citation Rates to Measure Influence at the Article Level.” Before we delve into the details and look at some real data, ….
August 30, 2016
This month, NIH published the projected fiscal year 2017 stipend guidelines for postdoctoral trainees and fellows supported by National Research Service Awards (NRSAs). For NRSA-supported postdocs with less than one year’s experience, the stipend level will increase to $47,484. In keeping with the recommendation of the Biomedical Research Workforce Working Group of the NIH Advisory Committee to the Director, stipend levels then increase dependent on years of postdoctoral experience. ….
August 24, 2016
We are most appreciative of the feedback we’ve received, through the blog and elsewhere, on NIH support of model organism research. In part 1 of this series, we mentioned that we asked two separate groups to analyze NIH applications and awards. In parts 1 and 2 we primarily focused on R01-based data that were curated and analyzed by our Office of Portfolio Analysis. In part 3, we show results from a broader range of research project grant (RPG) data that were prepared and analyzed by our Office of Research Information Systems. This group used an automated thesaurus-based text mining system which delves into not only public data such as project titles, abstracts, public health relevance statements, but also the specific aims contained in RPG applications. ….
August 3, 2016
We were pleased to hear the feedback on our previous post on NIH-funded model-organism research. One question a number of you asked is: what’s happening with research involving mouse models? Thanks to additional work by colleagues in NIH’s Office of Portfolio Analysis (OPA) and Office of Extramural Research/Office of Research Information Systems, I’m excited to … Continue reading “A Look at NIH Support for Model Organisms, Part Two”
July 28, 2016
In the spring, I attended my first NIH Regional Seminar on Program Funding and Grants Administration. I greatly enjoyed meeting with a diverse group of scientists and science administrators. During two “Open Mike” sessions, I had the opportunity to engage in rich conversations with attendees on topics I frequently include on this blog. The conversations were enjoyable and insightful – there’s nothing like discussing such important issues like funding trends, research accountability, and grants policy face-to-face with new and early career scientists. …. Why am I writing about a seminar that took place in May? Because I have some good news for those of you who didn’t get a chance to come to Baltimore! NIH is hosting a second Regional Seminar this year, from October 26-28 …..
July 22, 2016
In order to develop and implement data-driven policy, we need to carefully analyze our data to understand the “stories behind our metrics.” Without analyzing our data to know what’s going on, we’re essentially flying blind! A group of authors from the NIH Office of Extramural Research sought to investigate the stories behind peer review scoring and why some grant applications are more likely to be funded than others. They extended analyses previously reported by NIH’s Office of Extramural Research and National Institute of General Medical Studies. Last month, they published their analysis of over 123,000 competing R01 applications and described the correlations of individual component peer review scores – significance, investigator(s), innovation, approach, and environment – with subsequent overall impact score, and funding outcome. ….
July 14, 2016
Wangler, et al. recently published an article in Genetics on NIH funding for model organism research involving Drosophila. The authors extracted grant information from NIH ExPORTER and looked for the word “Drosophila” in either the title or abstract. By this approach the authors found that NIH support for Drosophila-based research is declining.
We chose to investigate further trends in NIH support for Drosophila and other model organism research. Two groups of NIH staff used two different approaches. Our Office of Research Information Systems (ORIS) used an automated thesaurus-based text mining system which mines not only project titles and abstracts but also the specific aims contained in the application; this is the system we use to generate “Research Condition and Disease Category” (or RCDC) tables, which are publicly posted to the NIH RePORT website. In a separate effort, our Office of Portfolio Analysis (OPA) supplemented a different text mining algorithm with extensive manual curation. Both methods – the wholly automated thesaurus-based text mining approach and the manual curation supplemented text mining approach – yielded similar findings. In this blog, we will present the results of the manually curated approach. ….
June 30, 2016
Back in January we talked about whether there is an advantage to working up to the last minute and submitting your grant application on the deadline. From the perspective of review outcomes, there was no advantage. In fact, applications submitted at the last minute seemed somewhat less likely to be discussed. Need another reason to apply early (by early we mean days, not hours, before a deadline)? We still see applications that fail ….
June 24, 2016
A few months ago, a researcher told me about his experiences with the relatively new NIH policy by which investigators are allowed to submit what we have come to call “virtual A2s.” Under NIH’s previous single resubmission policy, if an investigator’s de novo R01 grant application (called an “A0”) was not funded, they had one chance to submit a revision (called an “A1”). If the A1 application was unsuccessful, the applicant was required to make significant changes in the application compared to the previous submissions. NIH took measures to turn away subsequent submissions that were materially similar to the unfunded A1. Under NIH’s current policy, investigators may resubmit a materially similar application as a new submission after the A1 submission. We will call these applications “virtual A2s.” The researcher told me that his virtual A2 did not fare well; although his A0 and A1 had received good scores (though not good enough for funding), the virtual A2 was not discussed. He wondered, just how likely is it for a virtual A2 to be successful? ….
June 14, 2016
We were pleased to see the interest in our recent blog on the unique number of investigators applying for and receiving NIH research project grants (RPGs). Some of you (through the blog page or through other media) have asked about whether we have similar data for our Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) program. We have generated analogous figures for SBIR and STTR grants, and today’s post shares this investigation of the question, “How many unique researchers are seeking SBIR/STTR funding?” ….