estForest: Discrete Survival Random Forest Fitting

In discSurv: Discrete Time Survival Analysis

Discrete Survival Random Forest Fitting

Description

Wrapper for estimation of discrete survival random forest. Several preprocessing options such as time-dependent covariates are available.

Usage

estForest(
  dataShort,
  dataTransform = "dataLong",
  formulaVariable = ~timeInt,
  timeColumn,
  eventColumn,
  idColumn = NULL,
  timeAsFactor = FALSE,
  storeAugData = TRUE,
  responseAsFactor = TRUE,
  ...
)

Arguments

dataShort	Original data set in short format with each row corresponding to one independent observation (class "data.frame").
dataTransform	Specification of the data transformation function from short to long format (class "character"). There are two available options: Without time dependent covariates ("dataLong") and with time dependent covariates ("dataLongTimeDep"). The default is set to the former.
formulaVariable	Specifies the right hand side of the regression formula (class "formula"). The default is to use the discrete time variable, which corresponds to a covariate free hazard. It is recommended to always include the discrete time variable "timeInt".
timeColumn	Character giving the column name of the observed times. It is required that the observed times are discrete (class "integer").
eventColumn	Column name of the event indicator (class "character"). It is required that this is a binary variable with 1=="event" and 0=="censored".
idColumn	Name of column of identification number of persons (class "character"). Default is set to use function dataLong, that does not need this argument.
timeAsFactor	Should the time intervals be coded as factor (class "logical")? Default is FALSE. In the default settings the column is treated as quantitative variable (class "numeric").
storeAugData	Should the augmented data set be saved (class "logical")? Defaults is TRUE. The data set is available as attribute "augData".
responseAsFactor	Should the response be converted to factor? Default is TRUE. Representation as factor is technically important for classification split rules such as Gini index. For details see ranger.
...	Specification of additional arguments in function ranger.

Details

Variables in argument formulaVariable need to be separated by "+ ". For example, if the two variables timeInt and X1 should be included, the formula would be "~ timeInt + X1". The variable timeInt is constructed before estimation of the model.

Value

Returns an object of class "ranger".

Author(s)

Thomas Welchowski [e-mail]

References

\insertRef

schmidHellingerdiscSurv

See Also

dataLong, dataLongTimeDep, ranger

Examples

# Example with unemployment data
library(Ecdat)
data(UnempDur)

# Select subsample
SubUnempDur <- UnempDur[1:100, ]

# Estimate discrete survival random forest
estRFModel <- estForest(dataShort = SubUnempDur, dataTransform = "dataLong", 
formulaVariable =~ timeInt + age + ui + logwage + ui, 
eventColumn = "censor1", timeColumn = "spell")
estRFModel

discSurv documentation built on April 29, 2026, 9:07 a.m.