Computational methods for comparing two binary diagnostic tests in the presence of partial verification of the disease

Autor:	P. Femia Marzo, J.D. Luna del Castillo, J. A. Roldán Nofuentes
Rok vydání:	2009
Předmět:	Statistics and Probability Computational Mathematics McNemar's test Binomial (polynomial) Verification bias Partial verification Statistics Expectation–maximization algorithm Binary number Diagnostic test Statistics Probability and Uncertainty Confidence interval Mathematics
Zdroj:	Computational Statistics. 24:695-718
ISSN:	1613-9658 0943-4062
DOI:	10.1007/s00180-009-0155-y
Popis:	In the presence of partial verification of the disease, confidence interval estimation for the difference of sensitivities and specificities cannot be carried out by applying confidence intervals for the difference of binomial proportions, and the comparison of the accuracy of the two binary tests cannot be carried out by applying McNemar’s test. In this article we propose two methods for comparing the accuracy of two binary tests in the presence of partial verification of the disease. The first method is based on the application of the EM and SEM algorithms, and the second method consists of the calculation of confidence intervals for the difference in sensitivities and specificities applying confidence intervals for the difference in the two binomial proportions from the last table obtained applying the EM algorithm. We carried out simulation experiments in order to study and compare the coverage of several confidence intervals for the difference of the sensitivities and specificities.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9fc21467b76f55f29ae89a7fc6f47736 https://doi.org/10.1007/s00180-009-0155-y Zobrazit plný text záznamu Full text from SpringerLink