predictLifeYearsLost: Predicting life years lost (cumulative cumulative incidences)...

In pec: Prediction Error Curves for Risk Prediction Models in Survival Analysis

Predicting life years lost (cumulative cumulative incidences) in competing risk models.

Description

Function to extract predicted life years lost 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

predictLifeYearsLost(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 predictLifeYearsLost 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 positive value and in rows the values should be increasing.

Author(s)

Thomas A. Gerds [e-mail]

See Also

predictSurvProb, predictEventProb.

Examples

library(pec)
library(riskRegression)
library(survival)
library(prodlim)
train <- SimCompRisk(100)
test <- SimCompRisk(10)
fit <- CSC(Hist(time,cause)~X1+X2,data=train,cause=1)
predictLifeYearsLost(fit,newdata=test,times=seq(1:10),cv=FALSE,cause=1)

pec documentation built on April 11, 2023, 5:55 p.m.