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 tab.paired.

alpha

Significance level alpha used to compute 100(1-alpha)%-confidence intervals, the default is 0.05.

Value

A list containing:

ppv

A list with test1 (the positive predictive value of test 1), test2 (the positive predictive value of test 2), rppv (the relative positive predictive value, computed as test1 / test2), se.log.rppv (the standard error of the logarithm of rppv), lcl.rppv (the lower confidence limit of rppv), ucl.rppv (the upper confidence limit of rppv), the test.statistic and the corresponding p.value.

npv

A list with test1 (the negative predictive value of test 1), test2 (the negative predictive value of test 2), rnpv (the relative negative predictive value, computed as test1 / test2), 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.

method

The name of the method used to compare predictive values, here “relative predictive values (rpv)”.

alpha

The significance level alpha used to compute 100(1-alpha)%-confidence intervals for rppv and rnpv, 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.

See Also

pv.gs and pv.wgs.

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"]

[Package DTComPair version 1.0.3 Index]