coxphw
or
coxph
Compute generalized concordance probabilities with accompanying
confidence intervals for objects of class coxphw
or coxph
.
concord(fit, digits = 4)
A matrix with estimates of the generalized concordance probability with accompanying confidence intervalls for each explanatory variable in the model.
an object of class coxphw
.
integer indicating the number of decimal places to be used. Default is 4.
Daniela Dunkler
The generalized concordance probability is defined as \(P(T_i < T_j | x_i = x_j + 1)\) with \(T_i\) and \(T_j\) as survival times of randomly chosen subjects with covariate values \(x_i\) and \(x_j\), respectively. Assuming that \(x_i\) and \(x_j\) are 1 and 0, respectively, this definition includes a two-group comparison.
If proportional hazards can be assumed, the generalized concordance probability can also
be derived from Cox proportional hazards regression (coxphw
with template = "PH"
or coxph
) or weighted Cox regression as suggested by Xu and O'Quigley (2000)
(coxphw
with template = "ARE"
).
If in a fit to coxphw
the betafix
argument was used, then for the
fixed parameters only the point estimates are given.
Dunkler D, Schemper M, Heinze G. (2010) Gene Selection in Microarray Survival Studies Under Possibly Non-Proportional Hazards. Bioinformatics 26:784-90.
Xu R and O'Quigley J (2000). Estimating Average Regression Effect Under Non-Proportional Hazards. Biostatistics 1, 423-439.
coxphw
data("gastric")
fit <- coxphw(Surv(time, status) ~ radiation, data = gastric, template = "AHR")
concord(fit)
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