# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "MRStdCRT" in publications use:' type: software license: GPL-3.0-only title: 'MRStdCRT: Model-Robust Standardization in Cluster-Randomized Trials' version: 0.1.3 doi: 10.32614/CRAN.package.MRStdCRT abstract: 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) . 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) . authors: - family-names: Tong given-names: Jiaqi - family-names: Li given-names: Changjun email: changjun.li@yale.edu - family-names: Fang given-names: Xi - family-names: Cheng given-names: Chao - family-names: Lee given-names: Kenneth M. - family-names: Wang given-names: Bingkai - family-names: Li given-names: Fan repository: https://cran.r-universe.dev repository-code: https://github.com/deckardt98/MRStdCRT commit: 54265c8780b8fb9cc88b4c561583b2df826029cd url: https://github.com/deckardt98/MRStdCRT date-released: '2026-10-30' contact: - family-names: Li given-names: Changjun email: changjun.li@yale.edu