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Dependence Between Two Diagnostic Tests with Copula Function Approach: A Simulation Study
Authors:José Rafael Tovar  Jorge Alberto Achcar
Affiliation:1. Uiversidad del Rosario , Clinical Research Group;2. and Department of Statistics, Instituto de Matemática, Estatística e Computa??o , Campinas , SP , Brazil;3. and Department of Statistics, Instituto de Matemática, Estatística e Computa??o , Campinas , SP , Brazil;4. Department of Social Medicine, Faculdade de Medicina de Ribeir?o Preto (FMRP) , University of S?o Paulo , Riber?o Preto , SP , Brazil
Abstract:
The study of the dependence between two medical diagnostic tests is an important issue in health research since it can modify the diagnosis and, therefore, the decision regarding a therapeutic treatment for an individual. In many practical situations, the diagnostic procedure includes the use of two tests, with outcomes on a continuous scale. For final classification, usually there is an additional “gold standard” or reference test. Considering binary test responses, we usually assume independence between tests or a joint binary structure for dependence. In this article, we introduce a simulation study assuming two dependent dichotomized tests using two copula function dependence structures in the presence or absence of verification bias. We compare the test parameter estimators obtained under copula structure dependence with those obtained assuming binary dependence or assuming independent tests.
Keywords:Bayesian analysis  Copula functions  Dependent diagnostic tests  Farlie–Gumbel–Morgenstern (FGM) copula  Gumbel copula
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