title: Maximum likelihood estimation of reviewers' acumen in central review setting: categorical data.
abstract: Successfully evaluating pathologists' acumen could be very useful in improving the concordance of their calls on histopathologic variables. We are proposing a new method to estimate the reviewers' acumen based on their histopathologic calls. The previously proposed method includes redundant parameters that are not identifiable and results are incorrect. The new method is more parsimonious and through extensive simulation studies, we show that the new method relies less on the initial values and converges to the true parameters. The result of the anesthetist data set by the new method is more convincing.
authors: MedImmune LLC, Gaithersburg, MD 20878, USA. ZhaoW@medimmune.com
authors: Wei
authors: W
authors: Zhao
authors: James M
authors: JM
authors: Boyett
authors: Mehmet
authors: M
authors: Kocak
authors: David W
authors: DW
authors: Ellison
authors: Yanan
authors: Y
authors: Wu
mesh_terms: D000465:Algorithms; D000758:Anesthesia; D002983:Clinical Competence; D003198:Computer Simulation; D016013:Likelihood Functions; D010336:Pathology