listSLWrappers: Explains model averaging wrappers for super learning

In MAMI: Model Averaging and Model Selection after Multiple Imputation

Description

Explains model averaging wrappers which can be used in conjunction with package SuperLearner (and tmle and ltmle)

Usage

listSLWrappers()

Author(s)

Michael Schomaker

Examples

## Not run: 
listSLWrappers()
library(SuperLearner) # needs to be installed
SL.library <- c("SL.glm","SL.stepAIC", "SL.mean", "SL.step.interaction", "SL.mma.int", "SL.jma")
SL.library2 <- c("SL.glm","SL.stepAIC", "SL.mean", "SL.step.interaction", "SL.lae2")

data(Prostate)
P1 <- SuperLearner(Y=Prostate[,9], X=Prostate[,-9], SL.library = SL.library, verbose=T)
P2 <- SuperLearner(Y=Prostate[,5], X=Prostate[,-5], family="binomial", SL.library = SL.library2, verbose=T)
P2$coef

## End(Not run)

MAMI documentation built on May 6, 2019, 3:02 p.m.