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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