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Checks if model is a null-model (intercept-only), i.e. if the conditional part of the model has no predictors.

Usage

is_nullmodel(x)

Arguments

x

A model object.

Value

TRUE if x is a null-model, FALSE otherwise.

Examples

model <- lm(mpg ~ 1, data = mtcars)
is_nullmodel(model)
#> [1] TRUE

model <- lm(mpg ~ gear, data = mtcars)
is_nullmodel(model)
#> [1] FALSE

if (require("lme4")) {
  model <- lmer(Reaction ~ 1 + (Days | Subject), data = sleepstudy)
  is_nullmodel(model)

  model <- lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy)
  is_nullmodel(model)
}
#> [1] FALSE