wfe: Weighted Linear Fixed Effects Regression Models for Causal Inference

Provides a computationally efficient way of fitting weighted linear fixed effects estimators for causal inference with various weighting schemes. Weighted linear fixed effects estimators can be used to estimate the average treatment effects under different identification strategies. This includes stratified randomized experiments, matching and stratification for observational studies, first differencing, and difference-in-differences. The package implements methods described in Imai and Kim (2017) "When should We Use Linear Fixed Effects Regression Models for Causal Inference with Longitudinal Data?", available at <https://imai.princeton.edu/research/FEmatch.html>.

Version: 1.6
Depends: R (≥ 2.11.0)
Imports: utils, arm, Matrix, MASS, methods
Published: 2017-07-18
Author: In Song Kim [aut, cre], Kosuke Imai [aut], Erik Wang [aut]
Maintainer: In Song Kim <insong at mit.edu>
BugReports: https://github.com/insongkim/wfe/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: wfe results

Downloads:

Reference manual: wfe.pdf
Package source: wfe_1.6.tar.gz
Windows binaries: r-devel: wfe_1.6.zip, r-release: wfe_1.6.zip, r-oldrel: wfe_1.6.zip
OS X binaries: r-release: wfe_1.6.tgz, r-oldrel: wfe_1.6.tgz
Old sources: wfe archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=wfe to link to this page.