performance (version 0.3.0)

compare_performance: Model Performance

Description

See the documentation for your object's class:

• Frequentist Regressions

• Mixed models

• Bayesian models

• CFA / SEM lavaan models

compare_performance() computes indices of model performance for different models at once and hence allows comparison of indices across models.

Usage

compare_performance(..., metrics = "all", verbose = TRUE)
model_performance(model, ...)

Arguments

...

Arguments passed to or from other methods, resp. for compare_performance(), one or multiple model objects (also of different classes).

metrics

Can be "all" or a character vector of metrics to be computed. See related documentation of object's class for details.

verbose

Toggle off warnings.

model

Statistical model.

Value

For model_performance(), a data frame (with one row) and one column per "index" (see metrics). For compare_performance(), the same data frame with one row per model.

Details

If all models were fit from the same data, compare_performance() returns an additional column named BF, which shows the Bayes factor (see bayesfactor_models) for each model against the denominator model. The first model is used as denominator model, and its Bayes factor is set to NA to indicate the reference model.

Examples

# NOT RUN {
library(lme4)

m1 <- lm(mpg ~ wt + cyl, data = mtcars)
model_performance(m1)

m2 <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
m3 <- lmer(Petal.Length ~ Sepal.Length + (1 | Species), data = iris)
compare_performance(m1, m2, m3)

data(iris)
lm1 <- lm(Sepal.Length ~ Species, data = iris)
lm2 <- lm(Sepal.Length ~ Species + Petal.Length, data = iris)
lm3 <- lm(Sepal.Length ~ Species * Petal.Length, data = iris)
compare_performance(lm1, lm2, lm3)

# }