plot_maihda: Plot MAIHDA Model Results

In MAIHDA: Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy

Plot MAIHDA Model Results

Description

Creates various plots for visualizing MAIHDA model results including caterpillar plots, variance partition coefficient comparisons, observed vs. shrunken estimates, and predicted subgroup values with confidence intervals.

Usage

plot_maihda(
  object,
  type = c("caterpillar", "vpc", "obs_vs_shrunken", "predicted"),
  summary_obj = NULL,
  n_strata = 50,
  ...
)

Arguments

object	A maihda_model object from fit_maihda().
type	Character string specifying plot type: "caterpillar": Caterpillar plot of stratum random effects "vpc": Variance partition coefficient visualization "obs_vs_shrunken": Observed vs. shrunken stratum means "predicted": Predicted values for each stratum with confidence intervals
summary_obj	Optional maihda_summary object from summary_maihda(). If NULL, will be computed.
n_strata	Maximum number of strata to display in caterpillar plot or predicted plot. Default is 50. Use NULL for all strata.
...	Additional arguments (not currently used).

Value

A ggplot2 object.

Examples

strata_result <- make_strata(maihda_sim_data, vars = c("gender", "race"))
model <- fit_maihda(health_outcome ~ age + (1 | stratum), data = strata_result$data)

# Caterpillar plot
plot_maihda(model, type = "caterpillar")

# VPC plot
plot_maihda(model, type = "vpc")

# Observed vs shrunken plot
plot_maihda(model, type = "obs_vs_shrunken")

# Predicted values with confidence intervals
plot_maihda(model, type = "predicted")

MAIHDA documentation built on April 5, 2026, 5:06 p.m.