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The latenetwork package provides tools for causal inference under noncompliance with treatment assignment and network interference of unknown form. The package enables to implement the instrumental variables (IV) estimation for the local average treatment effect (LATE) type parameters via inverse probability weighting (IPW) using the concept of instrumental exposure mapping (IEM) and the framework of approximate neighborhood interference (ANI). For more details, see Hoshino and Yanagi (2023) “Causal inference with noncompliance and unknown interference”.


Get the package from CRAN:


or from GitHub:

# install.packages("devtools") # if needed
devtools::install_github("tkhdyanagi/latenetwork", build_vignettes = TRUE)


For more details, see the package vignettes with:


# Getting Started with the latenetwork Package

# Review of Causal Inference with Noncompliance and Unknown Interference
vignette("review", package = "latenetwork")


  • Hoshino, T. and Yanagi, T., 2023. Causal inference with noncompliance and unknown interference. arXiv preprint arXiv:2108.07455. Link