@misc{10481/69534,
year = {2021},
url = {http://hdl.handle.net/10481/69534},
abstract = {A binary diagnostic test is a medical test that is applied to an individual in order to
determine the presence or the absence of a certain disease and whose result can be positive or
negative. A positive result indicates the presence of the disease, and a negative result indicates
the absence. Positive and negative predictive values represent the accuracy of a binary diagnostic
test when it is applied to a cohort of individuals, and they are measures of the clinical accuracy of
the binary diagnostic test. In this manuscript, we study the comparison of the positive (negative)
predictive values of two binary diagnostic tests subject to a paired design through confidence intervals.
We have studied confidence intervals for the difference and for the ratio of the two positive (negative)
predictive values. Simulation experiments have been carried out to study the asymptotic behavior
of the confidence intervals, giving some general rules for application. We also study a method to
calculate the sample size to compare the parameters using confidence intervals. We have written a
program in R to solve the problems studied in this manuscript. The results have been applied to the
diagnosis of colorectal cancer.},
publisher = {MDPI},
keywords = {Binary diagnostic test},
keywords = {Confidence interval},
keywords = {Positive predictive value},
keywords = {Negative predictive value},
keywords = {Sample size},
title = {Confidence Intervals and Sample Size to Compare the Predictive Values of Two Diagnostic Tests},
doi = {10.3390/math9131462},
author = {Roldán Nofuentes, José Antonio and Regad, Saad Bouh},
}