clusteredinterference: Causal Effects from Observational Studies with Clustered Interference

Estimating causal effects from observational studies assuming clustered (or partial) interference. These inverse probability-weighted estimators target new estimands arising from population-level treatment policies. The estimands and estimators are introduced in Barkley et al. (2017) <arXiv:1711.04834>.

Package details

AuthorBrian G. Barkley [aut, cre] (<>), Bradley Saul [ctb]
MaintainerBrian G. Barkley <>
Package repositoryView on CRAN
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clusteredinterference documentation built on May 1, 2019, 9:26 p.m.