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:

2024-03-01

Dependencies

Imports/Depends/LinkingTo/Enhances (4)
R bayestestR >= 0.13.2 insight >= 0.19.8 datawizard >= 0.9.1

Suggests (59)
AER afex BayesFactor bayesplot betareg bigutilsr blavaan brms car carData CompQuadForm correlation cplm dbscan estimatr fixest flextable forecast ftExtra gamm4 ggplot2 glmmTMB Hmisc httr ICS ICSOutlier ISLR ivreg lavaan lme4 lmtest loo mclogit mclust metadat metafor mlogit multimode nestedLogit nonnest2 ordinal parameters >= 0.21.4 patchwork pscl psych quantreg qqplotr randomForest rempsyc rmarkdown rstanarm rstantools sandwich see survey testthat >= 3.2.1 tweedie VGAM withr >= 3.0.0

Suggests (59)

AER

afex

BayesFactor

bayesplot

betareg

bigutilsr

blavaan