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wfe (version 1.9.1)

Weighted Linear Fixed Effects Regression Models for Causal Inference

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 .

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Version

Install

install.packages('wfe')

Monthly Downloads

221

Version

1.9.1

License

GPL (>= 2)

Maintainer

Last Published

April 17th, 2019

Functions in wfe (1.9.1)

pwfe

Fitting the Weighted Fixed Effects Model with Propensity Score Weighting
wfe

Fitting the Weighted Fixed Effects Model for Causal Inference