MRStdCRT: Model-Robust Standardization in Cluster-Randomized Trials
Implements model-robust standardization for cluster-randomized trials (CRTs). Provides functions that standardize user-specified regression models to estimate marginal treatment effects. The targets include the cluster-average and individual-average treatment effects, with utilities for variance estimation and example simulation datasets. Methods are described in Li, Tong, Fang, Cheng, Kahan, and Wang (2025) <doi:10.1002/sim.70270>. Inverse-cluster-size weighted outcome models are available for generalized estimating equations and linear or generalized linear mixed models. The outcome models can use common fitting weights for both estimands or inverse-cluster-size weights for the cluster-average effect and no weights for the individual-average effect. Inference retains the original standardization framework and paired cluster jackknife. Related cluster-size saturated models are described in the arXiv preprint by Lee, Harhay, and Li (2026) <doi:10.48550/arXiv.2608.28943>.
| Version: |
0.1.3 |
| Depends: |
R (≥ 4.1) |
| Imports: |
dplyr (≥ 1.0.0), geepack (≥ 1.3-2), lme4 (≥ 1.1-25), nlme (≥ 3.1-150), magrittr (≥ 2.0.0), rlang (≥ 1.0.0), stats, WeMix (≥ 4.0.3) |
| Suggests: |
knitr, rmarkdown |
| Published: |
2026-10-30 |
| DOI: |
10.32614/CRAN.package.MRStdCRT |
| Author: |
Jiaqi Tong [aut],
Changjun Li [aut, cre],
Xi Fang [aut],
Chao Cheng [aut],
Kenneth M. Lee [aut],
Bingkai Wang [aut],
Fan Li [aut] |
| Maintainer: |
Changjun Li <changjun.li at yale.edu> |
| BugReports: |
https://github.com/deckardt98/MRStdCRT/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/deckardt98/MRStdCRT |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
MRStdCRT results |
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