ludecke2021performance.pdf (461.76 kB)
performance: an R package for assessment, comparison and testing of statistical models
journal contribution
posted on 2023-06-10, 06:10 authored by Daniel Lüdecke, Mattan Ben-Shachar, Indrajeet Patil, Philip Waggoner, Dominique MakowskiDominique MakowskiA crucial part of statistical analysis is evaluating a model’s quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many competing models. Upon investigation, fit indices should also be reported both visually and numerically to bring readers in on the investigative effort. The performance R-package (R Core Team, 2021) provides utilities for computing measures to assess model quality, many of which are not directly provided by R’s base or stats packages. These include measures like R2, intraclass correlation coefficient (ICC), root mean squared error (RMSE), or functions to check for vexing issues like overdispersion, singularity, or zeroinflation. These functions support a large variety of regression models including generalized linear models, (generalized) mixed-effects models, their Bayesian cousins, and many others.
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Publication status
- Published
File Version
- Published version
Journal
Journal of Open Source SoftwareISSN
2475-9066Publisher
The Open JournalExternal DOI
Issue
60Volume
6Page range
a3139 1-8Department affiliated with
- Psychology Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2023-02-06First Open Access (FOA) Date
2023-02-06First Compliant Deposit (FCD) Date
2023-02-04Usage metrics
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