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Plot MAIHDA Model Results

Source: R/plot_maihda.R
plot.maihda_model.Rd

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

Usage

# S3 method for class 'maihda_model'
plot(
  x,
  type = c("all", "vpc", "obs_vs_shrunken", "predicted", "risk_vs_effect",
    "effect_decomp", "ternary", "prediction_deviation"),
  summary_obj = NULL,
  n_strata = 50,
  ...
)

Arguments

x

A maihda_model object from fit_maihda().

type

Character string specifying plot type:

  • "vpc": Variance partition coefficient visualization

  • "obs_vs_shrunken": Observed vs. shrunken stratum means

  • "predicted": Predicted values for each stratum with confidence intervals

  • "risk_vs_effect": Quadrant scatterplot comparing overall risk to intersectional effect

  • "effect_decomp": Visualizes additive vs intersectional deviation from global mean

  • "ternary": Ternary plot analyzing the dimensional breakdown of variance

  • "prediction_deviation": Detailed deviation panels for individuals or strata

  • "all": Generate all available plots (default if not specified)

summary_obj

Optional maihda_summary object from summary(). If NULL, will be computed.

n_strata

Maximum number of strata to display in predicted plot. Default is 50. Use NULL for all strata.

...

Additional arguments (not currently used).

Value

A ggplot2 object, or a list of ggplot2 objects if type = "all".

Examples

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

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


# Generate all plots
plots <- plot(model)





#> Warning: Removing Layer 2 ('PositionNudge'), as it is not an approved position (for ternary plots) under the present ggtern package.


# }