validate.cph {Design}R Documentation

Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit

Description

This is the version of the validate function specific to models fitted with cph or psm. Statistics validated include the Nagelkerke R^2, D_{xy}, slope shrinkage, the discrimination indexD [(model L.R. chi-square - 1)/L], the unreliability index U = (difference in -2 log likelihood between uncalibrated X beta and X beta with overall slope calibrated to test sample) / L, and the overall quality index Q = D - U. L is -2 log likelihood with beta=0. The "corrected" slope can be thought of as shrinkage factor that takes into account overfitting. See predab.resample for the list of resampling methods.

Usage

# fit <- cph(formula=Surv(ftime,event) ~ terms, x=TRUE, y=TRUE, ...)
## S3 method for class 'cph':
validate(fit,method="boot",
                         B=40,bw=FALSE,rule="aic",type="residual",
                         sls=.05,aics=0,pr=FALSE,dxy=FALSE,u,tol=1e-9, ...)

## S3 method for class 'psm':
validate(fit, method="boot",B=40,
                   bw=FALSE,rule="aic",type="residual",sls=.05,aics=0,pr=FALSE,
                   dxy=FALSE,tol=1e-12, rel.tolerance=1e-5, maxiter=15, ...)

Arguments

fit a fit derived cph. The options x=TRUE and y=TRUE must have been specified. If the model contains any stratification factors and dxy=TRUE, the options surv=TRUE and time.inc=u must also have been given, where u is the same value of u given to validate.
method see validate
B
rel.tolerance
maxiter
bw
rule
type
sls
aics
pr
tol
... see validate or predab.resample
dxy set to TRUE to validate Somers' D_{xy} using rcorr.cens, which takes longer.
u must be specified if the model has any stratification factors and dxy=TRUE. In that case, strata are not included in X beta and the survival curves may cross. Predictions at time t=u are correlated with observed survival times. Does not apply to validate.psm.

Value

matrix with rows corresponding to D_{xy}, Slope, D, U, and Q, and columns for the original index, resample estimates, indexes applied to whole or omitted sample using model derived from resample, average optimism, corrected index, and number of successful resamples.

Side Effects

prints a summary, and optionally statistics for each re-fit (if pr=TRUE)

Author(s)

Frank Harrell
Department of Biostatistics, Vanderbilt University
f.harrell@vanderbilt.edu

See Also

validate, predab.resample, fastbw, Design, Design.trans, calibrate, rcorr.cens, cph, coxph.fit

Examples

n <- 1000
set.seed(731)
age <- 50 + 12*rnorm(n)
label(age) <- "Age"
sex <- factor(sample(c('Male','Female'), n, TRUE))
cens <- 15*runif(n)
h <- .02*exp(.04*(age-50)+.8*(sex=='Female'))
dt <- -log(runif(n))/h
e <- ifelse(dt <= cens,1,0)
dt <- pmin(dt, cens)
units(dt) <- "Year"
S <- Surv(dt,e)

f <- cph(S ~ age*sex, x=TRUE, y=TRUE)
# Validate full model fit
validate(f, B=10)               # normally B=150

# Validate a model with stratification.  Dxy is the only
# discrimination measure for such models, by Dxy requires
# one to choose a single time at which to predict S(t|X)
f <- cph(S ~ rcs(age)*strat(sex), 
         x=TRUE, y=TRUE, surv=TRUE, time.inc=2)
validate(f, dxy=TRUE, u=2, B=10)   # normally B=150
# Note u=time.inc

[Package Design version 2.0-11 Index]