causalEffect-class: causalEffect class

Description

causalEffect class

causalEffect constructor function

Usage

causalEffect(data, causalWeights, model.outputs, augment.estimate, call)

Value

an object of class causalEffect

Arguments

data: an object of class dataHolder
causalWeights: an object of class causalWeights
model.outputs: Outputs of the estimate_model() function
augment.estimate: Is the estimate to be the augmented (doubly robust) estimator? TRUE/FALSE
call: the call used to calculate the treatment effects

Slots

estimate: The estimated treatment effect.

estimand

The estimand of interest

weights

The weights as an object of class causalWeights

augmentedData

The data as a data.frame with variables weights, y_obs, y_0, y_1, y_hat_0, y_hat_1, x, and z. See details for more info.

fit

The fitted model if present. See details.

call

The call from the estimate_effect() function.

Details

The variables in slot augmentedData are

weights: The causalWeights targeting the causal estimand.
y_obs: The vector of the observed outcomes for each observation
y_0: The outcome under the control condition. Missingness respects the design of the experiment. i.e., \(Y(0) | Z = 1\) = NA.
y_hat_0: The conditional mean outcome under the control condition. Estimated from a model.
y_hat_1: The conditional mean outcome under the treatment condition. Estimated from a model.
x: The columns denoting the covariates.
z: The treatment indicator.

The slot fit is a list with slots control, treated, and overall_sample. Control and treated will be filled if estimate.separately is TRUE in estimate_effect. overall_sample will be filled if estimate.separately is FALSE.