Dear All,
I am trying to calculate a 95% confidence interval for the difference in two
c statistics (or equivalently D statistics). In Stata I gather that this
can be done using the lincom command. Is there anything similar in R?
As you can see below I have two datasets (that are actually two independent
subsets of the same data) and the respective c statistics for the variables
in both cases. What I would now like to do is to prove that there is no
statistically significant difference between the statistics (between the dev
and val datasets.)
Any help would be much appreciated.
> rdev <- rcorrcens(Surv(stimes1,eind1)~gendat1+neurodat1)
> rdev
Somers' Rank Correlation for Censored Data Response
variable:Surv(stimes1, eind1)
C Dxy aDxy SD Z P n
gendat1 0.534 0.069 0.069 0.017 3.98 0.0001 1500
neurodat1 0.482 -0.036 0.036 0.011 3.18 0.0015 1500
> rval <- rcorrcens(Surv(stimes2,eind2)~gendat2+neurodat2)
> rval
Somers' Rank Correlation for Censored Data Response
variable:Surv(stimes2, eind2)
C Dxy aDxy SD Z P n
gendat2 0.543 0.085 0.085 0.017 4.94 0e+00 1500
neurodat2 0.481 -0.038 0.038 0.011 3.44 6e-04 1500
Many thanks,
Laura
P.S. I'm using Windows XP, R 2.9.2
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