In the grant peer review process we can distinguish various evaluation stages in which assessors judge applications on a rating
scale. Bornmann & al.  show that latent Markov models offer a fundamentally good opportunity to model statistically peer review processes.
The main objective of this short communication is to test the influence of the applicants’ gender on the modeling of a peer
review process by using latent Markov models. We found differences in transition probabilities from one stage to the other
for applications for a doctoral fellowship submitted by male and female applicants.