Estimação bayesiana para medidas de desempenho de testes diagnósticos
Resumo
In the medical area, diagnostic tests are used to classify a patient as positive or
negative with respect to a given disease. There are simple and more elaborate tests, each
one with a speci9ed rate of misclassi9cation.
To verify the accuracy of the medical tests, we could have comparisons with a "gold
stantard", here is a test with no error.
In many situations we could not have "gold standard", by ethical reasons or by chance
that the individual is disease free or by high costs of the test.
Joseph et al (1999) introduces a Bayesian approach that solves the lack of a gold
standard, by using latent variables. In this work, we introduce this Bayesian methodology
giving generalizations in the presence of covariates. A comparative study is made with
the presence or not of gold standard to check the accuracy of the medical tests. Some
diGerent proportions of patients without gold standard are considered in a simulation
study. Numerical examples are considered using the proposed methodology.
We conclude the dissertation assuming dependence among two or more tests.