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.

Tests Vignettes

Available Snapshots

This version of performance can be found in the following snapshots:

2024-11-20

Dependencies

Imports/Depends/LinkingTo/Enhances (4)
R bayestestR >= 0.15.0 insight >= 0.20.5 datawizard >= 0.13.0

Suggests (62)
AER afex BayesFactor bayesplot betareg bigutilsr blavaan brms car carData CompQuadForm correlation cplm dagitty dbscan DHARMa estimatr fixest flextable forecast ftExtra gamm4 ggdag glmmTMB >= 1.1.10 Hmisc httr2 ICS ICSOutlier ISLR ivreg lavaan lme4 lmtest loo mclogit mclust metadat metafor mlogit multimode nestedLogit nonnest2 ordinal parameters >= 0.21.6 patchwork pscl psych quantreg qqplotr randomForest RcppEigen rempsyc rmarkdown rstanarm rstantools sandwich see survey testthat >= 3.2.1 tweedie VGAM withr >= 3.0.0

Suggests (62)

AER

afex

BayesFactor

bayesplot

betareg

bigutilsr

blavaan