Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard.
Biometrics
; 79(2): 1546-1558, 2023 06.
Article
em En
| MEDLINE
| ID: mdl-35531799
ABSTRACT
Many different methods for evaluating diagnostic test results in the absence of a gold standard have been proposed. In this paper, we discuss how one common method, a maximum likelihood estimate for a latent class model found via the Expectation-Maximization (EM) algorithm can be applied to longitudinal data where test sensitivity changes over time. We also propose two simplified and nonparametric methods which use data-based indicator variables for disease status and compare their accuracy to the maximum likelihood estimation (MLE) results. We find that with high specificity tests, the performance of simpler approximations may be just as high as the MLE.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Modelos Estatísticos
/
Técnicas e Procedimentos Diagnósticos
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Biometrics
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos