rsimsum
The facts below are what the maker publishes about rsimsum, checked and dated. Our editors have not written about it yet.
The facts
Each one read from rsimsum's own pages, with the date it was checked.
What it does
- Audience
- The package is intended to help report and analyze simulation studies, including comparisons across methods and simulated scenarios.checked 12 Oct 2026
- Deployment
- desktopchecked 24 Sep 2026
- Documentation
- The project says rsimsum includes five vignettes.checked 11 Oct 2026
- Estimands
- The simsum function handles one estimand at a time, while multisimsum supports multiple estimands.checked 11 Oct 2026
- Installation
- The package can be installed from CRAN or as a development version from GitHub using remotes.checked 12 Oct 2026
- Integration
- The package uses ggplot2 for visualisations and extends its autoplot generic.checked 11 Oct 2026
- License
- The package is licensed under GPL (>= 3).checked 12 Oct 2026
- Missing values
- Missing values are excluded by default, and boundary values can be set to drop estimates or standard errors beyond those limits.checked 11 Oct 2026
- Monte Carlo error
- It computes Monte Carlo standard errors and confidence intervals based on them to help interpret simulation study results.checked 12 Oct 2026
- Multiple estimands
- The simsum function handles one estimand at a time, while multisimsum summarizes studies with multiple estimands.checked 12 Oct 2026
- Notable limitation
- The main simsum function handles simulation studies with a single estimand of interest at a time.checked 11 Oct 2026
- Plotting integration
- rsimsum uses ggplot2 to produce data visualizations.checked 12 Oct 2026
- Purpose
- rsimsum is an R package for computing summary statistics from simulation studies.checked 12 Oct 2026
- Regression models
- Nochecked 24 Sep 2026
- Scripting support
- Yeschecked 24 Sep 2026
- Statistical tests
- Yeschecked 24 Sep 2026
- Summary measures
- Available measures include bias, empirical and model based standard errors, relative precision, mean squared error, coverage, and power.checked 12 Oct 2026
- Summary statistics
- It can calculate bias, empirical and model-based standard errors, relative precision, relative error in model standard error, mean squared error, and coverage.checked 11 Oct 2026
- Support
- The project links to GitHub to report bugs.checked 12 Oct 2026
- Visualisations
- It uses ggplot2 to provide forest, lolly, zipper, scatter, Bland–Altman, ridgeline, heat, contour, and hexbin plots.checked 11 Oct 2026
- Visualizations
- Its plotting functions include forest, lolly, zipper, scatter, Bland–Altman, ridgeline, heat, contour, and hexbin plots.checked 12 Oct 2026
The company
- Founded
- 2018checked 19 Oct 2026
Money
- Free plan
- Yeschecked 24 Sep 2026
Where it runs
- Windows and macOS downloads
- CRAN lists Windows and macOS package binaries for download.checked 12 Oct 2026
