has_proportional_error_model function

has_proportional_error_model

Check if a model has a proportional error model

Multiple dependent variables are supported. By default the only (in case of one) or the first (in case of many) dependent variable is going to be checked.

has_proportional_error_model(model, dv = NULL)

Arguments

• model: (Model) The model to check
• dv: (str or Expr or numeric (optional)) Name or DVID of dependent variable. NULL for the default (first or only)

Returns

(logical) TRUE if the model has a proportional error model and FALSE otherwise

Examples

## Not run:

model <- load_example_model("pheno")
has_proportional_error_model(model)
## End(Not run)

See Also

has_additive_error_model : Check if a model has an additive error model

has_combined_error_model : Check if a model has a combined error model

has_weighted_error_model : Check if a model has a weighted error model