inferference: Methods for causal inference with interference
In inferference: Methods for Causal Inference with Interference
Description
Interference occurs when the treatment of one unit affects outcomes of other
units. This package provides methods for estimating causal effects in the
presence of interference. Currently it implements the IPW estimators
proposed by Tchetgen Tchetgen and Vanderweele (2012) (doi: 10.1177/0962280210386779)
and developed further in Heydrich-Perez et al. (2014) (doi: 10.1111/biom.12184).
References
Saul, B. and Hugdens, M. G. (2017).
A Recipe for inferference: Start with Causal Inference. Add Interference. Mix Well with R.
Journal of Statistical Software, 82(2), 1-21. doi: 10.18637/jss.v082.i02
inferference documentation built on April 21, 2021, 5:06 p.m.
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Description
Interference occurs when the treatment of one unit affects outcomes of other units. This package provides methods for estimating causal effects in the presence of interference. Currently it implements the IPW estimators proposed by Tchetgen Tchetgen and Vanderweele (2012) (doi: 10.1177/0962280210386779) and developed further in Heydrich-Perez et al. (2014) (doi: 10.1111/biom.12184).
References
Saul, B. and Hugdens, M. G. (2017). A Recipe for inferference: Start with Causal Inference. Add Interference. Mix Well with R. Journal of Statistical Software, 82(2), 1-21. doi: 10.18637/jss.v082.i02
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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