royston: Compute Royston's D for a Cox model

Description Usage Arguments Details Value References Examples

View source: R/royston.R

Description

Compute the D statistic proposed by Royston and Sauerbrei along with several pseudo- R square values.

Usage

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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

These values are called pseudo R-squared since they involve only the linear predictor, and not the outcome. R.D is the value that corresponsds the Royston and Sauerbrei D statistic. R.KO is the value proposed by Kent and O'Quigley, R.N is the value proposed by Nagelkerke, and C.GH corresponds to Goen and Heller's concordance measure.

An adjustment for D 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, the estimated standard error of D, and four pseudo R-squared values.

References

M. Goen and G. Heller, Concordance probability and discriminatory power in proportional hazards regression. Biometrika 92:965-970, 2005.

N. Nagelkerke, J. Oosting, J. and A. Hart, A simple test for goodness of fit of Cox's proportional hazards model. Biometrics 40:483-486, 1984.

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

Examples

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# An example used in Royston and Sauerbrei
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)

survival documentation built on Aug. 24, 2021, 5:06 p.m.