ce_estimate_ra_att: Causal inference with multiple treatments using RA for ATT...

In CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome

Causal inference with multiple treatments using RA for ATT effects

Description

The function ce_estimate_ra_att implements RA to estimate ATT effect with multiple treatments using observational data.

Usage

ce_estimate_ra_att(y, x, w, ndpost, reference_trt)

Arguments

y	A numeric vector (0, 1) representing a binary outcome.
x	A dataframe, including all the covariates but not treatments.
w	A numeric vector representing the treatment groups.
ndpost	A numeric value indicating the number of posterior draws.
reference_trt	A numeric value indicating reference treatment group for ATT effect.

Value

A summary of the effect estimates can be obtained with summary function. The output also contains a list of the posterior samples of causal estimands.

References

Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. URL: https://CRAN.R-project.org/package=dplyr

Andrew Gelman and Yu-Sung Su (2020). arm: Data Analysis Using Regression and Multilevel/Hierarchical Models. R package version 1.11-2. https://CRAN.R-project.org/package=arm

CIMTx documentation built on June 24, 2022, 9:07 a.m.