R: Compute Royston's D for a Cox model

royston {survival} | R Documentation

## Compute Royston's D for a Cox model

### Description

Compute the D statistic and R^2 for a coxph model, proposed by Royston and Sauerbrei

### Usage

    royston(fit, newdata, ties = TRUE, adjust = FALSE)

### Arguments

`fit` | a coxph fit
`newdata` | optional validation data set
`ties` | make a correction for ties in the risk score
`adjust` | adjust for possible overfitting

### Details

The adjustment is based on the ratio r= (number of events)/(number of coefficients). For models which have sufficient sample size (r>20) the adjustment will be small.

### Value

a vector containing the value of D, R^2_D and the estimated standard error of D.

### References

P. Royston and W. Sauerbrei, A new measure of prognostic separation in survival data. Statistics in Medicine 23:723-748, 2004.

### Examples

    # one of the examples from the paper
    pbc2 <- na.omit(pbc)  # no missing values
    cfit <- coxph(Surv(time, status==2) ~ age + log(bili) + edema + albumin +
                       stage + copper, data=pbc2, ties="breslow")
    royston(cfit)

[Package survival version 3.2-7 Index]