Freedom251 › Statistical Analysis Software
rsimsum
by rsimsum
What rsimsum is
rsimsum is a free R package for summarizing and reporting simulation studies on Windows and macOS desktops. It calculates bias, empirical and model-based standard errors, relative precision, relative error in model standard error, mean squared error, coverage, and power. Monte Carlo standard errors and confidence intervals are produced by default. The simsum function handles one estimand at a time, while multisimsum supports studies with multiple estimands. Missing values are excluded by default, and boundary settings can remove estimates or standard errors outside chosen limits. For visualization, rsimsum uses ggplot2 and extends its autoplot generic with forest, lolly, zipper, scatter, Bland–Altman, ridgeline, heat, contour, and hexbin plots. Installation is available from CRAN, or as a development version from GitHub through remotes. The package is licensed under GPL (>= 3), includes five vignettes, and links to GitHub for bug reports and contribution guidance. It is intended for comparing methods and simulated scenarios in simulation-study analysis.
Who it suits
It suits analysts and researchers working with simulation studies who use R on Windows or macOS. Users comparing multiple estimands can use multisimsum, while simsum is limited to one estimand at a time.
What it does well
- Free R package under GPL (>= 3)
- Monte Carlo errors and intervals by default
- Many simulation summary measures
- Extensive ggplot2 visualizations
- CRAN and GitHub installation options
What to know first
- simsum handles one estimand at a time
- Requires an R environment
- Desktop binaries listed for Windows and macOS
Verdict
rsimsum provides a broad set of simulation-study measures, default Monte Carlo uncertainty summaries, and varied ggplot2 visualizations at no cost. Its main functional constraint is that simsum processes one estimand at a time; multisimsum is available for multiple estimands.
Facts from rsimsum's own pages
- Audience
- The package is intended to help report and analyze simulation studies, including comparisons across methods and simulated scenarios. · ellessenne.github.io, 12 Oct 2026
- Deployment
- desktop · ellessenne.github.io, 24 Sept 2026
- Documentation
- The project says rsimsum includes five vignettes. · ellessenne.github.io, 11 Oct 2026
- Estimands
- The simsum function handles one estimand at a time, while multisimsum supports multiple estimands. · ellessenne.github.io, 11 Oct 2026
- Founded
- 2018 · ellessenne.github.io, 19 Oct 2026
- Free plan
- Yes · ellessenne.github.io, 24 Sept 2026
- Installation
- The package can be installed from CRAN or as a development version from GitHub using remotes. · ellessenne.github.io, 12 Oct 2026
- Integration
- The package uses ggplot2 for visualisations and extends its autoplot generic. · ellessenne.github.io, 11 Oct 2026
- License
- The package is licensed under GPL (>= 3). · ellessenne.github.io, 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. · ellessenne.github.io, 11 Oct 2026
- Monte Carlo error
- It computes Monte Carlo standard errors and confidence intervals based on them to help interpret simulation study results. · ellessenne.github.io, 12 Oct 2026
- Multiple estimands
- The simsum function handles one estimand at a time, while multisimsum summarizes studies with multiple estimands. · ellessenne.github.io, 12 Oct 2026
- Notable limitation
- The main simsum function handles simulation studies with a single estimand of interest at a time. · ellessenne.github.io, 11 Oct 2026
- Plotting integration
- rsimsum uses ggplot2 to produce data visualizations. · ellessenne.github.io, 12 Oct 2026
- Purpose
- rsimsum is an R package for computing summary statistics from simulation studies. · ellessenne.github.io, 12 Oct 2026
- Regression models
- No · ellessenne.github.io, 24 Sept 2026
- Scripting support
- Yes · ellessenne.github.io, 24 Sept 2026
- Statistical tests
- Yes · ellessenne.github.io, 24 Sept 2026
- Summary measures
- Available measures include bias, empirical and model based standard errors, relative precision, mean squared error, coverage, and power. · ellessenne.github.io, 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. · ellessenne.github.io, 11 Oct 2026
- Support
- The project links to GitHub to report bugs. · ellessenne.github.io, 12 Oct 2026
- Visualisations
- It uses ggplot2 to provide forest, lolly, zipper, scatter, Bland–Altman, ridgeline, heat, contour, and hexbin plots. · ellessenne.github.io, 11 Oct 2026
- Visualizations
- Its plotting functions include forest, lolly, zipper, scatter, Bland–Altman, ridgeline, heat, contour, and hexbin plots. · ellessenne.github.io, 12 Oct 2026
- Windows and macOS downloads
- CRAN lists Windows and macOS package binaries for download. · mirror.linux.ncsu.edu, 12 Oct 2026
Where rsimsum stands on Freedom251
- Statistical Analysis Software#46 of 106