

I am interested Andrea is whether you ever established why your R2 was 1.
I have had a similar situation previously.

My main issue though, which I'd be v grateful for advice on, is why I am obtaining such  negative values -0.3  for Somers Dxy  using validate.cph from the Design package given my value of Nagelkerke R2 is not so low 13.2%.

I have this output when fitting 6 variables all with p-values<0.01
I am wondering what the interpretation should be.
I know my Nagelkerke R2 isn't very good but I compare my results with the example from ?validate.cph and although I have a better R2 (13% v 9%) the Somers dxy from the example data set is much better, 38%, so certainly not negative !

 So my main question is : Why such a difference between explained variation, R2, and predictive ability: somers dxy ??

Obs     Events Model L.R.       d.f.          P      Score    Score P         R2
       471        228      66.36          6          0      73.41          0      0.132

....

>  validate(f, B=150,dxy=T)               # normally B=150

         index.orig      training         test     optimism index.corrected   n
Dxy   -0.3022537331 -0.3135032097 -0.292492573 -0.021010636   -0.2812430968 150
R2     0.1319445685  0.1431179294  0.122599605  0.020518324    0.1114262446 150
Slope  1.0000000000  1.0000000000  0.923340558  0.076659442    0.9233405576 150
D      0.0250864459  0.0276820092  0.023163167  0.004518842    0.0205676038 150
U     -0.0007676033 -0.0007725071  0.000610456 -0.001382963    0.0006153598 150
Q      0.0258540493  0.0284545164  0.022552711  0.005901805    0.0199522440 150


I also calculated the Schemper and Henderson V measure and obtained v=10.5%

I was  using the surev package of Lusa Lara; Miceli Rosalba; Mariani LuigiEstimation of predictive accuracy in survival analysis using R and S-PLUS.<http://www.biomedexperts.com/Abstract.bme/17601627/Estimation_of_predictive_accuracy_in_survival_analysis_using_R_and_S-PLUS>
Computer methods and programs in biomedicine 2007;87(2):132-7.
And my code was
library(surev)
pred.accuracy<-f.surev(f)
pred.accuracy

sorry if my question isn't clear - should I have included my sessionInfo for a methodological question ? (I'm a newbie)
many thanks for any advice

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