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)
- Version1.0.1
- R version≥ 3.2
- LicenseGPL-3
- Needs compilation?No
- Last release03/18/2019
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Team
Brian G. Barkley
Bradley Saul
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- Depends1 package
- Imports5 packages
- Suggests5 packages