Package: wfe 1.9.1

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.fas.harvard.edu/research/FEmatch.html>.

Authors:In Song Kim [aut, cre], Kosuke Imai [aut]

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wfe.pdf |wfe.html
wfe/json (API)

# Install 'wfe' in R:
install.packages('wfe', repos = c('https://insongkim.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/insongkim/wfe/issues

On CRAN:

2 exports 20 stars 4.38 score 13 dependencies 24 scripts 234 downloads

Last updated 5 years agofrom:d7c0b7668a. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 23 2024
R-4.5-win-x86_64OKSep 23 2024
R-4.5-linux-x86_64OKSep 23 2024
R-4.4-win-x86_64OKSep 23 2024
R-4.4-mac-x86_64OKSep 23 2024
R-4.4-mac-aarch64OKSep 23 2024
R-4.3-win-x86_64OKSep 23 2024
R-4.3-mac-x86_64OKSep 23 2024
R-4.3-mac-aarch64OKSep 23 2024

Exports:pwfewfe

Dependencies:abindarmbootcodalatticelme4MASSMatrixminqanlmenloptrRcppRcppEigen