predict.cmprsk: Calculate the Failure Time Probability from a Competing Risks...

In QHScrnomo: Construct Nomograms for Competing Risks Regression Models

Calculate the Failure Time Probability from a Competing Risks Regression Model

Description

Computes the predicted probability of the event of interest at a specified time point for a competing risks regression model fit by crr.fit. This function is adapted from predict.crr.

Usage

## S3 method for class 'cmprsk'
predict(object, newdata = NULL, time, lps, ...)

Arguments

object	A model fit by crr.fit
newdata	A data.frame for prediction containing values of covariates in the model. If missing, the model development dataset (object$cphdat) is used.
time	A single time point to calculate the failure probability
lps	Should the linear predictor be returned instead of the failure probability? Defaults to FALSE.
...	Additional arguments such as cov2 as in crr

Value

A vector of failure probabilities at the specified time point (or linear predictors if lps=TRUE) with length equal to the number of rows in newdata

Author(s)

Michael W. Kattan, Ph.D. and Changhong Yu.
Department of Quantitative Health Sciences, Cleveland Clinic

References

Fine JP and Gray RJ (1999) A proportional hazards model for the subdistribution of a competing risk. JASA 94:496-509.

See Also

crr.fit, predict.crr

Examples

dd <- datadist(prostate.dat)
options(datadist = "dd")
prostate.f <- cph(Surv(TIME_EVENT,EVENT_DOD == 1) ~ TX  + rcs(PSA,3) +
           BX_GLSN_CAT +  CLIN_STG + rcs(AGE,3) +
           RACE_AA, data = prostate.dat,
           x = TRUE, y = TRUE, surv = TRUE,time.inc = 144)
prostate.crr <- crr.fit(prostate.f, cencode = 0, failcode = 1)
predict(prostate.crr, time = 60)

QHScrnomo documentation built on May 29, 2024, 9:21 a.m.