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performance: Assessment of Regression Models Performance

Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models. References: Lüdecke et al. (2021) <doi:10.21105/joss.03139>.

Version: 0.12.4
Depends: R (≥ 3.6)
Imports: bayestestR (≥ 0.15.0), insight (≥ 0.20.5), datawizard (≥ 0.13.0), stats, utils
Suggests: AER, afex, BayesFactor, bayesplot, betareg, bigutilsr, blavaan, boot, brms, car, carData, CompQuadForm, correlation, cplm, dagitty, dbscan, DHARMa, estimatr, fixest, flextable, forecast, ftExtra, gamm4, ggdag, glmmTMB (≥ 1.1.10), graphics, Hmisc, httr2, ICS, ICSOutlier, ISLR, ivreg, lavaan, lme4, lmtest, loo, MASS, Matrix, mclogit, mclust, metadat, metafor, mgcv, mlogit, multimode, nestedLogit, nlme, nonnest2, ordinal, parallel, parameters (≥ 0.21.6), patchwork, pscl, psych, quantreg, qqplotr (≥ 0.0.6), randomForest, RcppEigen, rempsyc, rmarkdown, rstanarm, rstantools, sandwich, see (≥ 0.9.0), survey, survival, testthat (≥ 3.2.1), tweedie, VGAM, withr (≥ 3.0.0)
Published: 2024-10-18
DOI: 10.32614/CRAN.package.performance
Author: Daniel Lüdecke ORCID iD [aut, cre], Dominique Makowski ORCID iD [aut, ctb], Mattan S. Ben-Shachar ORCID iD [aut, ctb], Indrajeet Patil ORCID iD [aut, ctb], Philip Waggoner ORCID iD [aut, ctb], Brenton M. Wiernik ORCID iD [aut, ctb], Rémi Thériault ORCID iD [aut, ctb], Vincent Arel-Bundock ORCID iD [ctb], Martin Jullum [rev], gjo11 [rev], Etienne Bacher ORCID iD [ctb], Joseph Luchman ORCID iD [ctb]
Maintainer: Daniel Lüdecke <d.luedecke at uke.de>
BugReports: https://github.com/easystats/performance/issues
License: GPL-3
URL: https://easystats.github.io/performance/
NeedsCompilation: no
Language: en-US
Citation: performance citation info
Materials: README NEWS
In views: MixedModels
CRAN checks: performance results

Documentation:

Reference manual: performance.pdf

Downloads:

Package source: performance_0.12.4.tar.gz
Windows binaries: r-devel: performance_0.12.4.zip, r-release: performance_0.12.4.zip, r-oldrel: performance_0.12.4.zip
macOS binaries: r-release (arm64): performance_0.12.4.tgz, r-oldrel (arm64): performance_0.12.4.tgz, r-release (x86_64): performance_0.12.4.tgz, r-oldrel (x86_64): performance_0.12.4.tgz
Old sources: performance archive

Reverse dependencies:

Reverse imports: bruceR, CR2, dotwhisker, easystats, effectsize, ggstatsplot, MLMusingR, modelbased, modelsummary, multitool, piecewiseSEM, PLSDAbatch, psycModel, pubh, report, SCDA, see, sjPlot, sjstats, statsExpressions, ZLAvian
Reverse suggests: afex, archetyper, bayestestR, COINr, dominanceanalysis, domir, insight, JSmediation, MuMIn, panelsummary, parameters, ProFAST, rempsyc, specr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=performance to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.