Plot regression coefficients — model_metrics

The regression output comes from stats::lm.

Usage

model_metrics_plot(
  data,
  col,
  categorical,
  metric,
  interactions = NULL,
  diagnostics = FALSE,
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data: A tibble.
col: The target column holding metric values.
categorical: A tidy column selection holding categorical variables.
metric: A tidy column selection holding metric variables.
interactions: A vector of interaction effects to calculate. Each interaction effect should be provided as multiplication of the variables. Example: c(sd_gender * adopter).
labels: If TRUE (default) extracts labels from the attributes, see codebook.
clean: Prepare data by data_clean.
...: Placeholder to allow calling the method with unused parameters from effect_metrics.

Value

A volker list object containing volker plots

Examples

library(volker)
data <- volker::chatgpt

data |>
  filter(sd_gender != "diverse") |>
  model_metrics_plot(use_work, categorical = c(sd_gender, adopter), metric = sd_age)