Package: MRTAnalysis 0.1.2
Tianchen Qian
MRTAnalysis: Primary and Secondary Analyses for Micro-Randomized Trials
Estimates marginal causal excursion effects and moderated causal excursion effects for micro-randomized trial (MRT). Applicable to MRT with binary treatment options and continuous or binary outcomes. The method for MRT with continuous outcomes is the weighted centered least squares (WCLS) by Boruvka et al. (2018) <doi:10.1080/01621459.2017.1305274>. The method for MRT with binary outcomes is the estimator for marginal excursion effect (EMEE) by Qian et al. (2021) <doi:10.1093/biomet/asaa070>.
Authors:
MRTAnalysis_0.1.2.tar.gz
MRTAnalysis_0.1.2.tar.gz(r-4.5-noble)MRTAnalysis_0.1.2.tar.gz(r-4.4-noble)
MRTAnalysis_0.1.2.tgz(r-4.4-emscripten)MRTAnalysis_0.1.2.tgz(r-4.3-emscripten)
MRTAnalysis.pdf |MRTAnalysis.html✨
MRTAnalysis/json (API)
NEWS
| # Install 'MRTAnalysis' in R: |
| install.packages('MRTAnalysis', repos = 'https://cloud.r-project.org') |
- data_binary - A synthetic data set of an MRT with binary outcome
- data_mimicHeartSteps - A synthetic data set that mimics the HeartSteps V1 data structure to illustrate the use of [wcls()] function for continuous outcomes
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:67c6371397. Checks:1 OK, 2 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 23 2025 |
| R-4.5-linux | NOTE | Mar 23 2025 |
| R-4.4-linux | NOTE | Mar 23 2025 |
Dependencies:backportsbroomclicpp11dplyrfansigeepackgenericsgluelatticelifecyclemagrittrMASSpillarpkgconfigpurrrR6rlangrootSolvesandwichstringistringrtibbletidyrtidyselectutf8vctrswithrzoo
Citation
To cite package ‘MRTAnalysis’ in publications use:
Qian T, Xiang S, Cheng Z (2023). MRTAnalysis: Primary and Secondary Analyses for Micro-Randomized Trials. R package version 0.1.2, https://CRAN.R-project.org/package=MRTAnalysis.
Corresponding BibTeX entry:
@Manual{,
title = {MRTAnalysis: Primary and Secondary Analyses for
Micro-Randomized Trials},
author = {Tianchen Qian and Shaolin Xiang and Zhaoxi Cheng},
year = {2023},
note = {R package version 0.1.2},
url = {https://CRAN.R-project.org/package=MRTAnalysis},
}
Readme and manuals
MRTanalaysis
This package provides functions to conduct primary analysis (estimating marginal causal excursion effect and moderated causal excursion effect) for Micro-randomized Trials with continuous or binary outcomes.
Please read the vignettes for details on how to use this package.
The main functions are the following:
- wcls(): Primary analysis for continuous outcome. This is an implementation of the weighted and centered least squares method (the k=1 special case of Boruvka, A., Almirall, D., Witkiewitz, K., & Murphy, S. A. (2018). Assessing time-varying causal effect moderation in mobile health. Journal of the American Statistical Association, 113(523), 1112-1121.)
- emee(): Primary analysis for binary outcome. This is an implementation of the estimator for marginal excursion effect method (the Delta=1 special case of Qian, T., Yoo, H., Klasnja, P., Almirall, D., & Murphy, S. A. (2021). Estimating time-varying causal excursion effects in mobile health with binary outcomes. Biometrika, 108(3), 507-527.)
Additional functions that can be useful:
- emee2(): Primary analysis for binary outcome. This is a slightly altered version of emee(), where the treatment assignment indicator is also centered in the residual term. It would have similar (but not exactly the same) numerical output as emee(). This is the estimator based on which the sample size calculator for binary outcome MRT is developed. (See R package MRTSampleSizeBinary.)