estimateG: estimateG

Description Usage Arguments Value Examples

Description

This function computes the conditional treatment probabilities at both timepoints.

Usage

1
2
estimateG(validFold, folds, L0, L1, A0, A1, abar, SL.g, glm.g, stratify,
  return.models, SL.g.options, verbose, tolg, ...)

Arguments

L0

A data.frame featuring covariates measured at baseline.

L1

A data.frame featuring time-varying covariates measured at the first timepoint.

A0

A vector treatment delivered at baseline.

A1

A vector treatment deliver after L1 is measured.

abar

A vector of length 2 indicating the treatment assignment that is of interest.

SL.g

A vector or list specifying the SuperLearner library to be used to estimate the conditional probability of treatment at each time point. See SuperLearner package for details.

glm.g

A character specifying the right-hand side of the glm formula used to estimate the conditional probability of treatment at each time point. Only used if SL.g = NULL.

stratify

A boolean indicating whether to pool across treatment nodes or to estimate outcome regression separately in each category.

return.models

A boolean indicating whether the models for g00 should be returned with the output.

SL.g.options

A list of additional arguments passed to SuperLearner for condtional treatment probability fits.

tolg

A numeric indicating the truncation level for conditional treatment probabilities.

...

Other arguments (currently passed to SuperLearner).

Value

Returns a list with g0n, g1n, and the estimated model objects if return.models = TRUE

Examples

1
TO DO : add examples

benkeser/drinf documentation built on May 12, 2019, 11:59 a.m.