| predictEventProb {pec} | R Documentation |
Predicting event probabilities (cumulative incidences) in competing risk models.
Description
Function to extract event probability predictions from various modeling
approaches. The most prominent one is the combination of cause-specific Cox
regression models which can be fitted with the function cumincCox
from the package compRisk.
Usage
predictEventProb(object, newdata, times, cause, ...)
Arguments
object |
A fitted model from which to extract predicted event probabilities |
newdata |
A data frame containing predictor variable combinations for which to compute predicted event probabilities. |
times |
A vector of times in the range of the response variable, for which the cumulative incidences event probabilities are computed. |
cause |
Identifies the cause of interest among the competing events. |
... |
Additional arguments that are passed on to the current method. |
Details
The function predictEventProb is a generic function that means it invokes specifically designed functions depending on the 'class' of the first argument.
See predictSurvProb.
Value
A matrix with as many rows as NROW(newdata) and as many
columns as length(times). Each entry should be a probability and in
rows the values should be increasing.
Author(s)
Thomas A. Gerds tag@biostat.ku.dk
See Also
See predictSurvProb.
Examples
library(pec)
library(survival)
library(riskRegression)
library(prodlim)
train <- SimCompRisk(100)
test <- SimCompRisk(10)
cox.fit <- CSC(Hist(time,cause)~X1+X2,data=train)
predictEventProb(cox.fit,newdata=test,times=seq(1:10),cause=1)
## with strata
cox.fit2 <- CSC(list(Hist(time,cause)~strata(X1)+X2,Hist(time,cause)~X1+X2),data=train)
predictEventProb(cox.fit2,newdata=test,times=seq(1:10),cause=1)