Modeling Without a Gold Standard: Stratification with Stratum-Dependent Parameters

Authors

  • Francisco Louzada University of São Paulo
  • Gilberto de Araujo Pereira Federal University of Triângulo Mineiro
  • Márcia M. Ferreira-Silva Federal University of Triângulo Mineiro
  • Valdirene de Fátima Barbosa Federal University of Triângulo Mineiro
  • Helio de Moraes-Souza Federal University of Triângulo Mineiro
  • Gleici S. Castro Perdona University of São Paulo

DOI:

https://doi.org/10.57805/revstat.v12i1.145

Keywords:

absence of a gold standard, diagnostic test, identifiability, sample size, stratification

Abstract

Bayesian latent-class models have been widely applied for assessing the performance of diagnostic tests in the absence of a gold standard. We provide a short discussion on identifiability issues appearing under the absence of a gold standard, and construct an extension of the well-known Hui–Walter stratification model which allows for stratumdependent parameters. We illustrate our approach using a Chagas disease case study on blood donors from Brazil.

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Published

2014-04-01

How to Cite

Louzada , F., de Araujo Pereira , G., Ferreira-Silva , M. M., de Fátima Barbosa , V., de Moraes-Souza , H., & S. Castro Perdona , G. (2014). Modeling Without a Gold Standard: Stratification with Stratum-Dependent Parameters. REVSTAT-Statistical Journal, 12(1), 85–99. https://doi.org/10.57805/revstat.v12i1.145

Issue

Vol. 12 No. 1 (2014): REVSTAT-Statistical Journal

Section

Article

License

Copyright (c) 2014 REVSTAT-Statistical Journal

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.