Re: [R] negative Somers D from Design package

2009-07-15 Thread Frank E Harrell Jr
For the Cox model Dxy is the rank correlation between predicted log 
hazard and time to event.  As a high hazard means that the time to event 
is short, you need to negate Dxy for your purpose.


Frank


North, Bernard V wrote:

Dear R help

My problem is very similar to the analysis detailed here.
If we use the mayo dataset provided with the survivalROC package the estimate 
for Somer's Dxy is very negative -0.56.
The Nagelkerke R2 is positive though 0.32.
I know there is a difference between explained variation and predictive ability 
but I am surprised there is usch a difference given that even a non predictive 
model should have Dxy around 0.
Am I doing something wrong or is there an interpretation that makes sense ?

This is with the mayo data so its reproducible but the result with my data is 
very similar.
Many thanks in advance

library(survivalROC)
library(Design)
library(survival)
data(mayo)

 Sm <- Surv(mayo$time,mayo$censor)
fm <- cph( Sm ~ mayoscore4,mayo,x=T,y=T,surv=T )
validate(fm, B=150,dxy=T)
Iteration 1 

index.orig training test  optimism index.corrected   n
Dxy   -0.566027923 -0.55407 -0.566027923 -0.0006374833-0.565390440 150
R2 0.325860603  0.327350885  0.325860603  0.0014902826 0.324370320 150
Slope  1.0  1.0  0.987854765  0.0121452354 0.987854765 150
D  0.093398440  0.095166239  0.093398440  0.0017677983 0.091630642 150
U -0.001562582 -0.001579618  0.001150175 -0.0027297932 0.001167211 150
Q  0.094961022  0.096745857  0.092248266  0.0044975915 0.090463431 150



Dr Bernard North
Statistical Consultant
Statistical Advisory Service
Advice and Courses on Research Design and Methodology
Imperial College
South Kensington Campus
Room 845, 4th Floor
8 Princes Gardens
London SW7 1NA.

Tel: 020 7594 2034
Fax: 020 7594 1489
Email: bno...@imperial.ac.uk
Web:  www.ic.ac.uk/stathelp




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--
Frank E Harrell Jr   Professor and Chair   School of Medicine
 Department of Biostatistics   Vanderbilt University

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[R] negative Somers D from Design package

2009-07-15 Thread North, Bernard V
Dear R help

My problem is very similar to the analysis detailed here.
If we use the mayo dataset provided with the survivalROC package the estimate 
for Somer's Dxy is very negative -0.56.
The Nagelkerke R2 is positive though 0.32.
I know there is a difference between explained variation and predictive ability 
but I am surprised there is usch a difference given that even a non predictive 
model should have Dxy around 0.
Am I doing something wrong or is there an interpretation that makes sense ?

This is with the mayo data so its reproducible but the result with my data is 
very similar.
Many thanks in advance

library(survivalROC)
library(Design)
library(survival)
data(mayo)

 Sm <- Surv(mayo$time,mayo$censor)
fm <- cph( Sm ~ mayoscore4,mayo,x=T,y=T,surv=T )
validate(fm, B=150,dxy=T)
Iteration 1 

index.orig training test  optimism index.corrected   n
Dxy   -0.566027923 -0.55407 -0.566027923 -0.0006374833-0.565390440 150
R2 0.325860603  0.327350885  0.325860603  0.0014902826 0.324370320 150
Slope  1.0  1.0  0.987854765  0.0121452354 0.987854765 150
D  0.093398440  0.095166239  0.093398440  0.0017677983 0.091630642 150
U -0.001562582 -0.001579618  0.001150175 -0.0027297932 0.001167211 150
Q  0.094961022  0.096745857  0.092248266  0.0044975915 0.090463431 150



Dr Bernard North
Statistical Consultant
Statistical Advisory Service
Advice and Courses on Research Design and Methodology
Imperial College
South Kensington Campus
Room 845, 4th Floor
8 Princes Gardens
London SW7 1NA.

Tel: 020 7594 2034
Fax: 020 7594 1489
Email: bno...@imperial.ac.uk
Web:  www.ic.ac.uk/stathelp




[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.