pv.rpv {DTComPair} | R Documentation |
Comparison of Predictive Values using Relative Predictive Values
Description
Performs a test for differences in (positive and negative) predictive values of two binary diagnostic tests in a paired study design using relative predictive values, as proposed by Moskowitz and Pepe (2006).
Usage
pv.rpv(tab, alpha)
Arguments
tab |
An object of class |
alpha |
Significance level alpha used to compute 100(1-alpha)%-confidence intervals, the default is 0.05. |
Value
A list containing:
ppv |
named vector containing |
npv |
named vector containing |
Sigma |
Estimated variance-covariance matrix for {log(relative positive predictive value), log(relative negative predictive value)}. |
method |
Name of the method used to compare predictive values, here “relative predictive values (rpv)”. |
alpha |
Significance level alpha used to compute 100(1-alpha)%-confidence intervals for |
References
Moskowitz, C.S., and Pepe, M.S. (2006). Comparing the predictive values of diagnostic tests: sample size and analysis for paired study designs. Clin Trials, 3(3):272-9.
See Also
Examples
data(Paired1) # Hypothetical study data
ftable(Paired1)
paired.layout <- tab.paired(d=d, y1=y1, y2=y2, data=Paired1)
paired.layout
rpv.results <- pv.rpv(paired.layout)
str(rpv.results)
rpv.results
rpv.results$ppv["p.value"]