Aalen Johansen Competing Risks Learner

This learner estimates the Cumulative Incidence Function (CIF) for competing risks using the empirical Aalen-Johansen (AJ) estimator. The probability of transitioning to each competing event is computed via the survfit function.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

LearnerCompRisksAalenJohansen$new()
mlr_learners$get("cmprsk.aalen")
lrn("cmprsk.aalen")

Meta Information

• Task type: “cmprsk”

• Predict Types: “cif”

• Feature Types: “logical”, “integer”, “numeric”, “factor”

• Required Packages: mlr3, mlr3proba, survival

Parameters

Id	Type	Default	Levels
model	logical	FALSE	TRUE, FALSE

References

Aalen, O O, Johansen, Soren (1978). “An empirical transition matrix for non-homogeneous Markov chains based on censored observations.” Scandinavian journal of statistics, 141–150.

Super classes

mlr3::Learner -> mlr3proba::LearnerCompRisks -> LearnerCompRisksAalenJohansen

Methods

Public methods

• LearnerCompRisksAalenJohansen$new()

• LearnerCompRisksAalenJohansen$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$configure()
• mlr3::Learner$encapsulate()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$reset()
• mlr3::Learner$selected_features()
• mlr3::Learner$train()

---

Method new()

Creates a new instance of this R6 class.

Usage

LearnerCompRisksAalenJohansen$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerCompRisksAalenJohansen$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.