pv.rpv: 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)

Value

A list containing:

ppv: named vector containing test1 (the positive predictive value of test 1), test2 (the positive predictive value of test 2), rppv (the relative positive predictive value, computed as test2 / test1), se.log.rppv (the standard error of the logarithm of rppv), lcl.rppv (lower confidence limit of rppv), ucl.rppv (the upper confidence limit of rppv), the test.statistic and the corresponding p.value.
npv: named vector containing test1 (the negative predictive value of test 1), test2 (the negative predictive value of test 2), rnpv (the relative negative predictive value, computed as test2 / test1), se.log.rnpv (the standard error of the logarithm of rnpv), lcl.rnpv (the lower confidence limit of rnpv), ucl.rnpv (the upper confidence limit of rnpv), the test.statistic and the corresponding p.value.
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 rppv and rnpv, the default is 0.05.

Arguments

tab: An object of class tab.paired.
alpha: Significance level alpha used to compute 100(1-alpha)%-confidence intervals, the default is 0.05.

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.

Examples

Run this code

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"]