@article{JSSv071c01,
title={LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions},
volume={71},
url={https://www.jstatsoft.org/index.php/jss/article/view/v071c01},
doi={10.18637/jss.v071.c01},
abstract={LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement) are binary. The method (Abadie 2003) involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects.},
number={1},
journal={Journal of Statistical Software, Code Snippets},
author={An, Weihua and Wang, Xuefu},
year={2016},
pages={1–13}
}