On the recordRead 12 Oct 202624 facts
rsimsum
rsimsum · founded 2018
On the record
- Audience
- The package is intended to help report and analyze simulation studies, including comparisons across methods and simulated scenarios.ellessenne.github.io · read 12 Oct 2026
- Deployment
- desktopellessenne.github.io · read 24 Sep 2026
- Documentation
- The project says rsimsum includes five vignettes.ellessenne.github.io · read 11 Oct 2026
- Estimands
- The simsum function handles one estimand at a time, while multisimsum supports multiple estimands.ellessenne.github.io · read 11 Oct 2026
- Installation
- The package can be installed from CRAN or as a development version from GitHub using remotes.ellessenne.github.io · read 12 Oct 2026
- Integration
- The package uses ggplot2 for visualisations and extends its autoplot generic.ellessenne.github.io · read 11 Oct 2026
- License
- The package is licensed under GPL (>= 3).ellessenne.github.io · read 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 · read 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 · read 12 Oct 2026
- Multiple estimands
- The simsum function handles one estimand at a time, while multisimsum summarizes studies with multiple estimands.ellessenne.github.io · read 12 Oct 2026
- Notable limitation
- The main simsum function handles simulation studies with a single estimand of interest at a time.ellessenne.github.io · read 11 Oct 2026
- Plotting integration
- rsimsum uses ggplot2 to produce data visualizations.ellessenne.github.io · read 12 Oct 2026
- Purpose
- rsimsum is an R package for computing summary statistics from simulation studies.ellessenne.github.io · read 12 Oct 2026
- Regression models
- Noellessenne.github.io · read 24 Sep 2026
- Scripting support
- Yesellessenne.github.io · read 24 Sep 2026
- Statistical tests
- Yesellessenne.github.io · read 24 Sep 2026
- Summary measures
- Available measures include bias, empirical and model based standard errors, relative precision, mean squared error, coverage, and power.ellessenne.github.io · read 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 · read 11 Oct 2026
