BarkleyBG/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>.
Getting started
Browse package contents
Package details |
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| Author | Brian G. Barkley [aut, cre] (0000-0003-1787-4735), Bradley Saul [ctb] |
| Maintainer | Brian G. Barkley <BarkleyBG@outlook.com> |
| License | GPL-3 |
| Version | 1.0.1 |
| URL | http://github.com/BarkleyBG/clusteredinterference |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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