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Maximum likelihood estimation of reviewers' acumen in central review setting: categorical data.
Zhao, Wei; Boyett, James M; Kocak, Mehmet; Ellison, David W; Wu, Yanan.
Afiliação
  • Zhao W; MedImmune LLC, Gaithersburg, MD 20878, USA. ZhaoW@medimmune.com
Theor Biol Med Model ; 8: 3, 2011 Mar 25.
Article em En | MEDLINE | ID: mdl-21439071
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Patologia / Competência Clínica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2011 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Patologia / Competência Clínica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2011 Tipo de documento: Article