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.
- Version1.9.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release04/17/2019
Documentation
Team
In Song Kim
MaintainerShow author detailsKosuke Imai
Insights
Last 30 days
This package has been downloaded 197 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
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Last 365 days
This package has been downloaded 2,655 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 41 downloads.
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Dependencies
- Imports3 packages