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: 0.12.3
Depends: R (≥ 3.6)
Imports: bayestestR (≥ 0.13.2), insight (≥ 0.20.2), datawizard (≥ 0.10.0), 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, 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 (≥ 0.8.2), survey, survival, testthat (≥ 3.2.1), tweedie, VGAM, withr (≥ 3.0.0)
Published: 2024-09-02
DOI: 10.32614/CRAN.package.performance
Author: Daniel Lüdecke ORCID iD [aut, cre] (@strengejacke), Dominique Makowski ORCID iD [aut, ctb] (@Dom_Makowski), Mattan S. Ben-Shachar ORCID iD [aut, ctb] (@mattansb), Indrajeet Patil ORCID iD [aut, ctb] (@patilindrajeets), Philip Waggoner ORCID iD [aut, ctb], Brenton M. Wiernik ORCID iD [aut, ctb] (@bmwiernik), Rémi Thériault ORCID iD [aut, ctb] (@rempsyc), 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_0.12.3.tar.gz
Windows binaries: r-devel: performance_0.12.3.zip, r-release: performance_0.12.3.zip, r-oldrel: performance_0.12.3.zip
macOS binaries: r-release (arm64): performance_0.12.3.tgz, r-oldrel (arm64): performance_0.12.3.tgz, r-release (x86_64): performance_0.12.3.tgz, r-oldrel (x86_64): performance_0.12.3.tgz
Old sources: performance archive

Reverse dependencies:

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

Linking:

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