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wfe  

Weighted Linear Fixed Effects Regression Models for Causal Inference
View on CRAN: Click here


Download and install wfe package within the R console
Install from CRAN:
install.packages("wfe")

Install from Github:
library("remotes")
install_github("cran/wfe")

Install by package version:
library("remotes")
install_version("wfe", "1.9.1")



Attach the package and use:
library("wfe")
Maintained by
In Song Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-12-13
Latest Update: 2019-04-17
Description:
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.fas.harvard.edu/research/FEmatch.html>.
How to cite:
In Song Kim (2011). wfe: Weighted Linear Fixed Effects Regression Models for Causal Inference. R package version 1.9.1, https://cran.r-project.org/web/packages/wfe. Accessed 25 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:00), 0.1 (2011-12-13 09:36), 1.0 (2012-07-18 22:12), 1.1 (2012-11-14 17:41), 1.2 (2013-02-06 16:10), 1.3 (2014-08-11 05:56), 1.6 (2017-07-19 00:05), 1.7 (2018-11-25 20:00), 1.8 (2019-01-09 13:00)
Other packages that cited wfe R package
View wfe citation profile
Other R packages that wfe depends, imports, suggests or enhances
Complete documentation for wfe
Functions, R codes and Examples using the wfe R package
Some associated functions: pwfe . wfe . 
Some associated R codes: functions.R . onAttach.R . pwfe.R . wfe.R .  Full wfe package functions and examples
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