simMetric: Metrics (with Uncertainty) for Simulation Studies that Evaluate Statistical Methods

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simMetric is an R package that provides metrics (and their Monte Carlo standard errors) for the assessment of statistical methods in simulation studies. This package includes metrics that are calculated as per this tutorial published by Tim Morris, Ian White and Michael Crowther. For an in-depth description on the calculation and interpretation, and how to perform a simulation study in general, refer to the tutorial.

Access rights

Access rights (MIT licence): Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Publications

Rex Parsons, publications https://eprints.qut.edu.au/view/person/Parsons,_Rex.html

Research areas

Biostatistics

Statistics

Simulation

Cite this collection

Parsons, Rex; (2022): simMetric: Metrics (with Uncertainty) for Simulation Studies that Evaluate Statistical Methods. Queensland University of Technology. (Software) https://doi.org/10.25912/RDF_1665114451679