Plot Prediction Deviation Panels — plot_prediction_deviation

Creates an advanced, publication-ready two-panel dashboard for visualizing predicted values and identifying deviant cases in linear, binomial, or ordinal models.

Usage

plot_prediction_deviation_panels(
  model,
  data = NULL,
  type = c("auto", "gaussian", "binomial", "ordinal"),
  ordinal_mode = c("surprise", "expected_score"),
  top_n_labels = 5,
  strata_info = NULL
)

Arguments

model: A fitted model object (e.g., from `lm()`, `glm()`, `MASS::polr()`, or `lme4::glmer()`).
data: The original data frame used to fit the model. If `NULL`, attempts to extract from the model.
type: Model type: "auto" (default), "gaussian", "binomial", or "ordinal".
ordinal_mode: For ordinal models: "surprise" (default, based on observation probability) or "expected_score".
top_n_labels: Number of extreme/deviant cases to label on the plot. Default is 5.
strata_info: Optional data frame of strata labels, generally extracted from `maihda_model` objects.

Value

A `patchwork` object containing two `ggplot2` panels.