Bind multiple model summaries for a grouped forest plot — bind_forest

Tidies multiple fitted models and stacks their fixed-effect coefficient tables into a single forest-plot data frame. The resulting data can be passed directly to ggforestplot(), where model labels are used as the grouping variable for dodged, color-coded estimates.

Usage

bind_forest_models(models, model_labels = NULL, exponentiate = NULL, ...)

Arguments

models: A non-empty list of fitted model objects supported by tidy_forest_model().
model_labels: Optional labels used to identify each model in the forest plot. Defaults to list names when present, otherwise "Model 1", "Model 2", and so on.
exponentiate: NULL, a single logical value, or one logical value per model. NULL uses the canonical scale inferred by tidy_forest_model() for each model.
...: Additional arguments passed to tidy_forest_model(), such as conf.level, intercept, term_labels, or sort_terms.

Value

A standardized forest-plot data frame with one row per model term and a group column containing the model labels.

Examples

if (requireNamespace("broom", quietly = TRUE)) {
  fit1 <- lm(mpg ~ wt + hp, data = mtcars)
  fit2 <- lm(mpg ~ wt + qsec, data = mtcars)

  bound <- bind_forest_models(
    list(Base = fit1, Adjusted = fit2)
  )

  ggforestplot(bound)
}