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  • 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
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