pec: predictEventProb – R documentation

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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.

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

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)

pec

Prediction Error Curves for Risk Prediction Models in Survival Analysis

v2020.11.17

GPL (>= 2)

Authors

Thomas A. Gerds

Initial release