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MRStdLCRT (version 0.1.0)

Model-Robust Standardization for Longitudinal Cluster-Randomized Trials

Description

Provides estimation and leave-one-cluster-out jackknife standard errors for four longitudinal cluster-randomized trial estimands: horizontal individual average treatment effect (h-iATE), horizontal cluster average treatment effect (h-cATE), vertical individual average treatment effect (v-iATE), and vertical cluster-period average treatment effect (v-cATE), using unadjusted and augmented (model-robust standardization) estimators. The working model may be fit using linear mixed models for continuous outcomes or generalized estimating equations and generalized linear mixed models for binary outcomes. Period inclusion for aggregation is determined automatically: only periods with both treated and control clusters are included in the construction of the marginal means and treatment effect contrasts. See Fang et al. (2025) .

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Version

Install

install.packages('MRStdLCRT')

Version

0.1.0

License

MIT + file LICENSE

Maintainer

Xi Fang

Last Published

January 15th, 2026

Functions in MRStdLCRT (0.1.0)

xo_b

Example crossover cluster-randomized trial dataset with binary outcome
plot.mrs

Plot method for mrs objects
print.mrs

Print method for mrs objects
xo_c

Example crossover cluster-randomized trial dataset with continuous outcome
sw_b

Example stepped wedge CRT dataset with binary outcome
summary.mrs

Summarize an mrs fit
sw_c

Example of stepped wedge CRT dataset for continuous outcome
mrstdlcrt_fit

Fit model-robust standardization for longitudinal CRTs