linear.TMLE.updater.speedglm: Linear TMLE glm updater

In osofr/estimtr: Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data

Description

Performs linear TMLE update using main-terms GLM (family=gaussian()), based on speedglm package. This function may be passed to fit_GCOMP / fit_TMLE function. May be also used as a separate learner for iTMLE.

Usage

linear.TMLE.updater.speedglm(Y, X, newX, family, obsWeights, ...)

## S3 method for class 'linear.TMLE.updater'
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 linear.TMLE.updater.speedglm.
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.