Assessing Proximal, Distal, and Mediated Causal Excursion Effects for Micro-Randomized Trials R package MRTAnalysis version 0.4.1 Provides methods to analyze micro-randomized trials (MRTs) with binary treatment options. Supports four types of analyses: (1) proximal causal excursion effects, including weighted and centered least squares (WCLS) for continuous proximal outcomes by Boruvka et al. (2018) <doi:10.1080/01621459.2017.1305274> and the estimator for marginal excursion effect (EMEE) for binary proximal outcomes by Qian et al. (2021) <doi:10.1093/biomet/asaa070>; (2) distal causal excursion effects (DCEE) for continuous distal outcomes using a two-stage estimator by Qian (2025) <doi:10.1093/biomtc/ujaf134>; (3) mediated causal excursion effects (MCEE) for continuous distal outcomes, estimating natural direct and indirect excursion effects in the presence of time-varying mediators by Qian (2025) <doi:10.48550/arXiv.2506.20027>; and (4) standardized proximal effect size estimation for continuous proximal outcomes, generalizing the approach in Luers et al. (2019) <doi:10.1007/s11121-017-0862-5> to allow adjustment for baseline and time-varying covariates for improved efficiency. Software Depends: R (>= 4.2) Imports: rootSolve, stats, geepack, sandwich, mgcv, randomForest, ranger, boot Suggests: knitr, rmarkdown, testthat (>= 3.0.0), SuperLearner, earth, dplyr Tianchen Qian <t.qian@uci.edu> Comprehensive R Archive Network (CRAN) Tianchen Qian [aut, cre] (ORCID: <https://orcid.org/0000-0003-4282-7826>), Shaolin Xiang [aut], Zhaoxi Cheng [aut], Xinyi Song [aut], John Dziak [aut], Audrey Boruvka [ctb] GPL-3 2026-01-24 application/tgz https://CRAN.R-project.org/package=MRTAnalysis doi:10.32614/CRAN.package.MRTAnalysis