MLCausal: Causal Inference Methods for Multilevel and Clustered Data
Provides an end-to-end workflow for estimating average treatment effects in clustered (multilevel) observational data. Core functionality includes cluster-aware propensity score estimation using fixed effects and Mundlak-style specifications, inverse probability weighting, within-cluster nearest-neighbor matching, covariate balance diagnostics at both individual and cluster-mean levels, outcome regression with cluster-robust standard errors, propensity score overlap visualization, and tipping-point sensitivity analysis for omitted cluster-level confounding.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats, sandwich (≥ 3.0-0), lmtest (≥ 0.9-38), ggplot2 (≥ 3.3.0), rlang (≥ 0.4.0) |
| Suggests: | testthat (≥ 3.0.0), knitr (≥ 1.36), rmarkdown (≥ 2.11) |
| Published: | 2026-04-15 |
| DOI: | 10.32614/CRAN.package.MLCausal (may not be active yet) |
| Author: | Subir Hait  [aut,
cre] |
| Maintainer: | Subir Hait <haitsubi at msu.edu> |
| BugReports: | https://github.com/causalfragility-lab/MLCausal/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/causalfragility-lab/MLCausal |
| NeedsCompilation: | no |
| Citation: | MLCausal citation info |
| Materials: | README |
| CRAN checks: | MLCausal results |
Documentation:
| Reference manual: | MLCausal.html , MLCausal.pdf |
| Vignettes: |
Introduction to MLCausal (source, R code) |
Downloads:
| Package source: | MLCausal_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
Linking:
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