SENSITIVITY AND SPECIFICITY OF DIAGNOSTIC TESTS IN DIFFERENT DEPENDENT SCENARIOS
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Abstract
Evaluation of diagnostic tests and validation of an instrument have focused on estimation of sensitivity and specificity. In practice, more than two diagnostic tests may be performed either sequentially or simultaneously in the same subject and it may be of interest to evaluate their performance in relation to a gold standard procedure. Another peculiar situation occurs when a diagnostic test is repeated multiple times to the same individual. In recent years there has been an increase of research related to the evaluation of diagnostic tests involving grouped data or other type of data dependency. Several statistical methods have been suggested and evaluated in order to correct the bias and the variance estimates of sensitivity and specificity in different dependency structures. In this work we summarized and compared some of the methods available in the literature for point and interval estimation for sensitivity and specificity when there are more than two diagnostic tests performed in the same individual, or when more than a measure of the same test is available for each individual. Simulation studies are conducted and a data analysis related to Ascaris infection is shown. In any data dependency scenario, the estimation methods need to take into account the correlation between multiple measurements of the same individual. Definition of new methods is needed to cope with the increased complexity of the data structure of studies considering, for example, multiple measurements across multiple diagnostic tests.
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