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.
Highlights
A diagnostic test is medical test that is applied to an individual in order to determine the presence of a certain disease
The dependency factors ε 1 and ε 0 do not have an important effect on the behavior of the confidence interval (CI) for the difference of the two negative predictive values
The following general rules of application can be given depending on the sample size, since the sample size is the only parameter controlled by the researcher: (a) apply the Wald CI for the difference of the positive predictive values whatever the sample size; (b) apply the Wald CI for the ratio of the two positive predictive values when the sample size is small, and apply the Wald CI, the logarithmic CI, the Fieller
Summary
A diagnostic test is medical test that is applied to an individual in order to determine the presence of a certain disease. A Wald-type CI for the difference of the two positive (negative) predictive values is obtained by inverting the contrast statistic of the hypothesis test studied by Wang et al [4]. The objective of this manuscript is study CIs to compare the positive (negative) predictive values of two BDTs subject to a paired design. The problem of calculating the sample size to compare the two positive (negative) predictive values through a CI is studied. This manuscript is structured in the following way.
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