Latent Markov modelling applied to grant peer review

Details Latent Markov modelling applied to grant peer review Latent Markov modelling applied to grant peer review

2006-04-03

arxiv.org/abs/math/0604039v1

Mathematics

Statistics Theory

Scientific paper

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.

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