Online Program Home
  My Program

Abstract Details

Activity Number: 349 - Contributed Poster Presentations: Section on Statistical Computing
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #325424
Title: Early Stage Investigator Policy Evaluation: The Statistical Necessities
Author(s): Rachael Walsh* and Robert Moore
Companies: National Institutes of Health, Office of Extramural Research and National Institutes of Health, Office of Extramural Research
Keywords: early stage investigator ; NIH grant funding ; policy evaluation
Abstract:

To assist new scientists in the transition to independent research careers, the National Institutes of Health (NIH) implemented an Early Stage Investigator (ESI) policy beginning with applications submitted in 2009. During the review process, the ESI designation segregates applications submitted by investigators within 10 years of completing their terminal degree or medical residency from applications submitted by more experienced investigators. Institutes/Centers can then give special consideration to ESI applications when making funding decisions. One goal of this policy is to increase the probability of newly emergent investigators receiving research support. Using direct matching algorithms to generate comparable groups pre- and post-policy implementation, generalized linear models were used to evaluate the ESI policy, comparing the probability of funding for ESI flagged applications from 2011 to 2015 to applications from 2004 to 2008 with similar characteristics. This paper addresses the statistical necessities of public policy evaluation, finding that the ESI policy stabilized the proportion of NIH funded newly emergent investigators. In the absence of the ESI policy, 54 percent of newly emergent investigators would not have received funding.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

 
 
Copyright © American Statistical Association