inferference: Methods for causal inference with interference

Description References


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) and developed further in Heydrich-Perez et al. (2014).


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 Nov. 25, 2017, 1:03 a.m.