Dear All,
Apologies if you have a seen a question like this from me before. I am hoping
that if I re-word my question more carefully someone may be able to offer more
help than the last time I asked something similar. I am using R 2.9.2 and
Windows XP.
I am trying to determine if there is a statistically significant difference
between two c-statistics (or equivalently D statistics). In Stata I gather
that this
can be done using the lincom command but I am not aware of anything similar in
R.
I am doing a simulation study and have simulated two datasets (independent). I
can obtain c-statistics for each variable in each dataset using this code:
> 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
Is there a way to determine if the c-statistics are significantly
different/similar to one another across data sets (i.e. I want to compare the
c-statistic for gendat1 with that for gendat2). I was considering using the
'tost' function within the equivalence package but that doesn't seem
appropriate either.
Many thanks,
Laura
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