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wfe

Weighted Linear Fixed Effects Regression Models for Causal Inference

v1.9.1 · Apr 17, 2019 · GPL (>= 2)

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>.

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LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-windows-x86_64

LazyData

  'LazyData' is specified without a 'data' directory
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Check History

NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-macos-x86_64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-windows-x86_64

LazyData

  'LazyData' is specified without a 'data' directory

Dependency Network

Dependencies Reverse dependencies arm Matrix MASS wfe

Version History

new 1.9.1 Mar 10, 2026