| ce_estimate_iptw_att {CIMTx} | R Documentation |
Causal inference with multiple treatments using IPTW for ATT effects
Description
The function ce_estimate_iptw_att implements
IPTW to estimate ATT effect with
multiple treatments using observational data.
Usage
ce_estimate_iptw_att(y, x, w, method, 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. |
method |
A character string. Users can selected from the
following methods including |
reference_trt |
A numeric value indicating reference treatment group for ATT effect. |
... |
Other parameters that can be passed through to functions. |
Value
A summary of the effect estimates can be obtained
with summary function. The weight distributions can be
visualized using plot function.
References
Venables, W. N. & Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth Edition. Springer, New York. ISBN 0-387-95457-0
Matthew Cefalu, Greg Ridgeway, Dan McCaffrey, Andrew Morral, Beth Ann Griffin and Lane Burgette (2021). twang: Toolkit for Weighting and Analysis of Nonequivalent Groups. R package version 2.5. URL:https://CRAN.R-project.org/package=twang
Noah Greifer (2021). WeightIt: Weighting for Covariate Balance in Observational Studies. R package version 0.12.0. URL:https://CRAN.R-project.org/package=WeightIt