dlr.regtest | 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(1-alpha)%-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(1-alpha)%-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):172-86.
DLR
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
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