When tests or portions of tests are scored subjectively by raters, a r
escoring will yield a change in the ratings of some examinees. In a te
st with a fixed passing score a rescoring will result in the change of
some pass/fail decisions. The number of changes depends on: the relia
bility of the rating system, the number of raters, the variability in
examinee abilities, the proportion of examinees that initially pass, a
nd the policy used to incorporate the rescore into the pass/fail decis
ion. In this study, we provide a model that facilitates the evaluation
of various rescoring strategies. We consider and compare the efficien
cy of three rescoring strategies: (1) rescore everyone, (2) rescore fa
ilures only, and (3) rescore within some range of the passing cutoff.
These rescoring strategies are evaluated by direct simulation. Additio
nally we consider the optimal allocation of rescores where the probabi
lity someone asks to be rescored is inversely proportional to the dist
ance from their initial score to the cutscore. This allocation is eval
uated via numerical integration. A further generalization of the basic
model is also considered in which a test is comprised of a mixture of
objectively and subjectively scored items.