predictEventProb: 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.

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.

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.

Examples

Run this code

# NOT RUN {
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)

# }