compare_performance: Model Performance

Description

See the documentation for your object's class:

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

Run this code

# 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)

# }