Predicting based on a rocTree model.

Source: R/predict.rocTree.R

The function gives predicted values with a rocTree fit.

# S3 method for rocTree
predict(object, newdata, type = c("survival",
  "hazard"), control = list(), ...)

Arguments

object

is an rocTree object.
newdata

is an optional data frame in which to look for variables with which to predict. If omitted, the fitted predictors are used. If the covariate observation time is not supplied, covariates will be treated as at baseline.
type

is an optional character string specifying whether to predict the survival probability or the cumulative hazard rate.
control

a list of control parameters. See 'details' for important special features of control parameters. See rocTree for more details.
...

for future developments.

Value

Returns a data.frame of the predicted survival probabilities or cumulative hazard.

Examples

data(simDat)
fit <- rocTree(Surv(Time, death) ~ z1 + z2, id = id, data = simDat, ensemble = FALSE)

## testing data
newdat <- data.frame(Time = sort(unique(simDat$Time)),
                     z2 = runif(1))
newdat$z1 <- 1 * (newdat$Time < median(newdat$Time))
head(newdat)
#>         Time      z2 z1
#> 1 0.07122299 0.80568  1
#> 2 0.08619285 0.80568  1
#> 3 0.11940614 0.80568  1
#> 4 0.12982798 0.80568  1
#> 5 0.14131532 0.80568  1
#> 6 0.14313760 0.80568  1

## Predict survival 
pred <- predict(fit, newdat)
plot(pred)

## Predict hazard
pred <- predict(fit, newdat, type = "hazard")
plot(pred)