pava.pred: Make predictions of predict functions in rows mononotone

In scheike/timereg: Flexible Regression Models for Survival Data

Make predictions of predict functions in rows mononotone

Description

Make predictions of predict functions in rows mononotone using the pool-adjacent-violators-algorithm

Usage

pava.pred(pred, increasing = TRUE)

Arguments

pred	predictions, either vector or rows of predictions.
increasing	increasing or decreasing.

Value

mononotone predictions.

Author(s)

Thomas Scheike

Examples

data(bmt); 

## competing risks 
add<-comp.risk(Event(time,cause)~platelet+age+tcell,data=bmt,cause=1)
ndata<-data.frame(platelet=c(1,0,0),age=c(0,1,0),tcell=c(0,0,1))
out<-predict(add,newdata=ndata,uniform=0)

par(mfrow=c(1,1))
head(out$P1)
matplot(out$time,t(out$P1),type="s")

###P1m <- t(apply(out$P1,1,pava))
P1monotone <- pava.pred(out$P1)
head(P1monotone)
matlines(out$time,t(P1monotone),type="s")

scheike/timereg documentation built on Jan. 25, 2023, 3:43 p.m.