Checks whether a list of models are nested models — is_nested

Checks whether a list of models are nested models, strictly following the order they were passed to the function.

Usage

is_nested_models(...)

Arguments

...: Multiple regression model objects.

Value

TRUE if models are nested, FALSE otherwise. If models are nested, also returns two attributes that indicate whether nesting of models is in decreasing or increasing order.

Details

The term "nested" here means that all the fixed predictors of a model are contained within the fixed predictors of a larger model (sometimes referred to as the encompassing model). Currently, is_nested_models() ignores random effects parameters.

Examples

m1 <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)
m2 <- lm(Sepal.Length ~ Species, data = iris)
m3 <- lm(Sepal.Length ~ Petal.Width, data = iris)
m4 <- lm(Sepal.Length ~ 1, data = iris)

is_nested_models(m1, m2, m4)
#> [1] TRUE
#> attr(,"is_nested_increasing")
#> [1] FALSE
#> attr(,"is_nested_decreasing")
#> [1] TRUE
is_nested_models(m4, m2, m1)
#> [1] TRUE
#> attr(,"is_nested_increasing")
#> [1] TRUE
#> attr(,"is_nested_decreasing")
#> [1] FALSE
is_nested_models(m1, m2, m3)
#> [1] FALSE