estimateQ: estimateQ

Description Usage Arguments Value Examples

Description

This function computes the conditional treatment probabilities at both timepoints.

Usage

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estimateQ(validFold, folds, L0, L1, L2, A0, A1, abar, SL.Q, SL.Q.options, glm.Q,
  glm.Q.options, return.models, verbose, stratify, ...)

Arguments

L0

A data.frame featuring covariates measured at baseline.

L1

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

L2

A vector outcome of interest

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.Q

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.

SL.Q.options

A list of additional arguments passed to SuperLearner for outcome regression fits.

glm.Q

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.Q = NULL.

glm.Q.options

A list of additional arguments passed to glm for the outcome regression fits. Typically, the family argument.

return.models

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

stratify

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

...

Other arguments (not currently used).

Value

Returns a list with Q2n, Q1n, and the estimated model objects if return.models = TRUE

Examples

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TO DO : add examples

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