MODELING WITHOUT A GOLD STANDARD: STRATIFICATION WITH STRATUM-DEPENDENT PARAMETERS

• 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 stratum-dependent parameters. We illustrate our approach using a Chagas disease case study on blood donors from Brazil. Key-Words: • absence of a gold standard; diagnostic test; identifiability; sample size; stratification. AMS Subject Classification