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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.
predictEventProb(object, newdata, times, cause, ...)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.
A fitted model from which to extract predicted event probabilities
A data frame containing predictor variable combinations for which to compute predicted event probabilities.
A vector of times in the range of the response variable, for which the cumulative incidences event probabilities are computed.
Identifies the cause of interest among the competing events.
Additional arguments that are passed on to the current method.
Thomas A. Gerds tag@biostat.ku.dk
The function predictEventProb is a generic function that means it invokes specifically designed functions depending on the 'class' of the first argument.
See predictSurvProb.
See predictSurvProb.
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)
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