r - How to calculate Somer's D / C-index for an external validation dataset given a ordinal response -

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i have fit proportional odds regression model using lrm function within harrell's 'rms' package. wondering how can calculate c-index / somer's d external validation dataset applied fitted model. these statistics can calculated fitted model directly using fitted.model$stats, unsure how them external validation dataset.

there appear built in function doing binary or survival responses in 'rms' package, val.prob & val.surv, can't find method ordinal response.

you should re-read documentation lrm. ordinal responses handled in function. run code using first example ?lrm generates "fit"-object:

pred.logit <- predict(fit) phat <- 1/(1+exp(-pred.logit)) > str(pred.logit)  named num [1:1000] na na na 0.234 0.577 ...  - attr(*, "names")= chr [1:1000] "1" "2" "3" "4" ... > str(fit$y)  named num [1:997] 0 1 0 1 1 0 0 0 0 0 ...  - attr(*, "names")= chr [1:997] "4" "5" "6" "7" ...  val.prob(phat[-(1:3)], y=fit$y, m=20, cex=.5)            dxy       c (roc)            r2             d      d:chi-sq           d:p   2.836172e-01  6.418086e-01  8.959553e-02  6.840647e-02  6.920125e+01  1.110223e-16              u      u:chi-sq           u:p             q         brier     intercept  -2.006018e-03 -1.591616e-12  1.000000e+00  7.041249e-02  2.315756e-01  5.977542e-14          slope          emax           s:z           s:p          eavg   1.000000e+00  1.956213e-13 -3.813108e-02  9.695832e-01  2.443947e-02  >

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