tidy_forest_model: Tidy a model object for forest plotting

In ggforestplotR: Publication-Ready Forest Plots with 'ggplot2'

Tidy a model object for forest plotting

Description

Uses broom::tidy() to convert a fitted model into forest-plot data.

Usage

tidy_forest_model(
  model,
  conf.int = TRUE,
  conf.level = 0.95,
  exponentiate = NULL,
  intercept = FALSE,
  term_labels = NULL,
  sort_terms = c("none", "descending", "ascending")
)

Arguments

model	A fitted model object supported by broom::tidy().
conf.int	Logical; if TRUE, request confidence intervals from broom::tidy().
conf.level	Confidence level for intervals.
exponentiate	Logical; passed through to broom::tidy().
intercept	Logical; if FALSE, drop the intercept term.
term_labels	Optional named vector used to relabel displayed terms. Names should match model term names and values are the labels to display.
sort_terms	How to sort rows: "none", "descending", or "ascending".

Value

A standardized coefficient data frame ready for ggforestplot().

Examples

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

  set.seed(123)
  logit_data <- data.frame(
    age = rnorm(250, mean = 62, sd = 8),
    bmi = rnorm(250, mean = 28, sd = 4),
    treatment = factor(rbinom(250, 1, 0.45), labels = c("Control", "Treatment"))
  )
  linpred <- -9 + 0.09 * logit_data$age + 0.11 * logit_data$bmi +
    0.9 * (logit_data$treatment == "Treatment")
  logit_data$event <- rbinom(250, 1, plogis(linpred))
  logit_fit <- glm(event ~ age + bmi + treatment, data = logit_data, family = binomial())

  tidy_forest_model(logit_fit, exponentiate = TRUE)
}

ggforestplotR documentation built on June 5, 2026, 5:07 p.m.