English

Latent Markov modelling applied to grant peer review

Statistics Theory 2007-06-13 v1 Statistics Theory

Abstract

In the grant peer review process we can distinguish various evaluation stages in which assessors judge applications on a rating scale. Research on this process that considers its multi-stage character scarcely exists. In this study we analyze 1954 applications for doctoral and post-doctoral fellowships of the Boehringer Ingelheim Fonds (B.I.F.), assessed in three stages (first: evaluation by an external reviewer; second: internal evaluation by a staff member; third: final decision by the B.I.F. Board of Trustees). The results show that an application only has a chance of approval if it was recommended for support in the first evaluation stage. Therefore, a form of triage or pre-screening seems desirable. We found differences in transition probabilities from one stage to the other for doctoral applicants submitted by males and females.

Cite

@article{arxiv.math/0604039,
  title  = {Latent Markov modelling applied to grant peer review},
  author = {Lutz Bornmann and Ruediger Mutz and Hans-Dieter Daniel},
  journal= {arXiv preprint arXiv:math/0604039},
  year   = {2007}
}
R2 v1 2026-07-22T17:33:44.166Z