rsq: r^2 measures for a a 'coxph' or 'survfit' model In dardisco/survMisc: Miscellaneous Functions for Survival Data

Description

r^2 measures for a a `coxph` or `survfit` model

Usage

 ```1 2 3 4 5 6 7``` ```rsq(x, ...) ## S3 method for class 'coxph' rsq(x, ..., sigD = 2) ## S3 method for class 'survfit' rsq(x, ..., sigD = 2) ```

Arguments

 `x` A `survfit` or `coxph` object. `sigD` significant digits (for ease of display). If `sigD=NULL`, will return the original numbers. `...` Additional arguments (not implemented).

Value

A `list` with the following elements:

 `cod` The coefficient of determination, which is R^2 = 1-exp((2/n).(L-L)) where L and L are the log partial likelihoods for the null and full models respectively and n is the number of observations in the data set. `mer` The measure of explained randomness, which is: R^2[mer] = 1-exp((2/m).(L-L)) where m is the number of observed events. `mev` The measure of explained variation (similar to that for linear regression), which is: R^2 = R^2[mer] / ( R^2[mer] + pi/6(1-R^2[mer]) )

References

Nagelkerke NJD, 1991. A Note on a General Definition of the Coefficient of Determination. Biometrika 78(3):691–92. JSTOR

O'Quigley J, Xu R, Stare J, 2005. Explained randomness in proportional hazards models. Stat Med 24(3):479–89. Wiley (paywall) Available at UCSD

Royston P, 2006. Explained variation for survival models. The Stata Journal 6(1):83–96. The Stata Journal

Examples

 ```1 2 3``` ```data("kidney", package="KMsurv") c1 <- coxph(Surv(time=time, event=delta) ~ type, data=kidney) cbind(rsq(c1), rsq(c1, sigD=NULL)) ```

dardisco/survMisc documentation built on May 14, 2019, 6:08 p.m.