README.md
In BarkleyBG/stabilizedinterference: Stabilized IPW Estimators for Causal Effects with Partial Interference
stabilizedinterference
The goal of stabilizedinterference is to estimate causal effects in the
presence of interference, with “stabilized” IPTW estimators as
introduced in Liu, Hudgens, and Becker-Dreps (2016)
Biometrika.
These estimators estimate causal effects in the presence of partial or
clustered interference, with estimates of the asymptotic variance from
standard M-estimation theory.
IPW estimators are implemented in the function estimateEffects()
This package is in working order, but currently under development.
Suggestions are welcome; thanks for your patience!
BarkleyBG/stabilizedinterference documentation built on May 23, 2019, 8:37 a.m.
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stabilizedinterference
The goal of stabilizedinterference is to estimate causal effects in the presence of interference, with “stabilized” IPTW estimators as introduced in Liu, Hudgens, and Becker-Dreps (2016) Biometrika.
These estimators estimate causal effects in the presence of partial or clustered interference, with estimates of the asymptotic variance from standard M-estimation theory.
IPW estimators are implemented in the function estimateEffects()
This package is in working order, but currently under development. Suggestions are welcome; thanks for your patience!
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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