iTMLE.updater.glm: iTMLE glm learner / updater

Description Usage Arguments

View source: R/TMLE_updaters.R

Description

Performs an SDR update using a main-terms GLM (logistic regression with stats::glm). This function is passed along as a separate learner to the SuperLearner implementation in origami package

Usage

1
2
3
4
iTMLE.updater.glm(Y, X, newX, family, obsWeights, ...)

## S3 method for class 'iTMLE.updater.glm'
predict(object, newdata, offset, ...)

Arguments

Y

Input outcomes

X

Input design matrix with training data. Must contain a column named "offset", which contains the offsets converted to logit-linear scale.

newX

Input design matrix with test data. Same requirement as for X: must contain a column named "offset", which contains the offsets converted to logit-linear scale.

family

Link function (ignored).

obsWeights

Row-specific weights

...

Additional arguments to be passed on to origami package.

object

Results of calling iTMLE.updater.glm.

newdata

Design matrix with test data for which predictions should be obtained. May contain a column named "offset", instead of it being passed as a separate argument.

offset

Offset (on logit scale if using logistic regression update).


osofr/estimtr documentation built on Jan. 25, 2022, 8:05 a.m.