文章基本信息

标题：LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions
本地全文：下载
作者：Weihua An ; Xuefu Wang
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2016
卷号：71
期号：1
页码：1-13
语种：English
出版社：University of California, Los Angeles
摘要：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.
关键词：instrumental variable;causal inference;compliers;local average response function