dlr.regtest {DTComPair}  R Documentation 
Performs a test for differences in (positive and negative) diagnostic likelihood ratios (DLRs) of two binary diagnostic tests in a paired study using a regression model approach proposed by Gu and Pepe (2009).
dlr.regtest(tab, alpha)
tab 
An object of class 
alpha 
Significance level alpha for 100(1alpha)%confidence intervals, the default is 0.05. 
The null hypothesis rDLR = DLR of Test 1 / DLR of Test 2 = 1 is tested with respect to both positive and negative DLRs of the two diagnostic tests.
This function calls DLR
, a general implementation of the method proposed by Gu and Pepe (2009).
A list containing
pdlr 
A list with

ndlr 
A list with

alpha 
The significance level alpha used to compute 100(1alpha)%confidence intervals for the 
method 
The name of the method used to compare the positive and negative DLRs, here “diagnostic likelihood regression model (regtest)”. 
Gu, W. and Pepe, M. S. (2009). Estimating the capacity for improvement in risk prediction with a marker. Biostatistics, 10(1):17286.
data(Paired1) # Hypothetical study data
ptab < tab.paired(d=d, y1=y1, y2=y2, data=Paired1)
ptab
dlr.results < dlr.regtest(ptab)
str(dlr.results)
dlr.results