A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review. (arXiv:2201.02539v1 [stat.ME])

Rankings and scores are two common data types used by judges to express
preferences and/or perceptions of quality in a collection of objects. Numerous
models exist to study data of each type separately, but no unified statistical
model captures both data types simultaneously without first performing data
conversion. We propose the Mallows-Binomial model to close this gap, which
combines a Mallows' $\phi$ ranking model with Binomial score models through
shared parameters that quantify object quality, a consensus ranking, and the …

application arxiv learning panel review statistical