acc.paired | R Documentation |
Sensitivity and specificity, (positive and negative) predictive values and (positive and negative) diagnostic likelihood ratios of a two binary diagnostic tests in a paired study design.
acc.paired(tab, alpha, method.ci, ...)
tab |
An object of class |
alpha |
Significance level alpha for 100(1-alpha)%-confidence intervals, the default is 0.05. |
method.ci |
A function used to compute the confidence intervals for sensitivity, specificity, and predictive values. The default is |
... |
Additional arguments, usually not required. |
The calculation of accuracy measures follows standard methodology, e.g. described in Pepe (2003) or Zhou et al. (2011).
The confidence intervals for sensitivity, specificity, and predictive values are computed using the methodology implemented in the function passed to the argument method.ci
.
Confidence intervals for diagnostic likelihood ratios are computed according to Simel et al. (1991).
A list of class acc.paired
:
Test1 |
A list of class |
Test2 |
A list of class |
Pepe, M. (2003). The statistical evaluation of medical tests for classifcation and prediction. Oxford Statistical Science Series. Oxford University Press, 1st edition.
Zhou, X., Obuchowski, N., and McClish, D. (2011). Statistical Methods in Diagnostic Medicine. Wiley Series in Probability and Statistics. John Wiley & Sons, Hoboken, New Jersey, 2nd edition.
tab.paired
,
print.acc.paired
,
acc.1test
.
data(Paired1) # Hypothetical study data
b1 <- tab.paired(d=d, y1=y1, y2=y2, data=Paired1)
b2 <- acc.paired(b1)
print(b2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.