Plot MID Component Functions with ggplot2

ggmid() is an S3 generic function for creating various visualizations from MID-related objects using ggplot2. For "mid" objects (i.e., fitted MID models), it visualizes a single component function specified by the term argument.

Usage

ggmid(object, ...)

# S3 method for class 'mid'
ggmid(
  object,
  term,
  type = c("effect", "data", "compound"),
  theme = NULL,
  intercept = FALSE,
  main.effects = FALSE,
  data = NULL,
  limits = c(NA, NA),
  jitter = 0.3,
  resolution = c(100L, 100L),
  ...
)

# S3 method for class 'mid'
autoplot(object, ...)

Arguments

object: a "mid" object to be visualized.
...: optional parameters passed to the main plotting layer.
term: a character string specifying the component function to be plotted.
type: the plotting style. One of "effect", "data" or "compound".
theme: a character string or object defining the color theme. See color.theme for details.
intercept: logical. If TRUE, the intercept is added to the MID values.
main.effects: logical. If TRUE, main effects are included in the interaction plot.
data: a data frame to be plotted with the corresponding MID values. If not provided, data is automatically extracted based on the function call.
limits: a numeric vector of length two specifying the limits of the plotting scale. NA values are replaced by the minimum and/or maximum MID values.
jitter: a numeric value specifying the amount of jitter for the data points.
resolution: an integer or vector of two integers specifying the resolution of the raster plot for interactions.

Value

ggmid.mid() returns a "ggplot" object.

Details

For "mid" objects, ggmid() creates a "ggplot" object that visualizes a component function of the fitted MID model.

The type argument controls the visualization style. The default, type = "effect", plots the component function itself. In this style, the plotting method is automatically selected based on the effect's type: a line plot for quantitative main effects; a bar plot for qualitative main effects; and a raster plot for interactions. The type = "data" option creates a scatter plot of data, colored by the values of the component function. The type = "compound" option combines both approaches, plotting the component function alongside the data points.

Examples

data(diamonds, package = "ggplot2")
set.seed(42)
idx <- sample(nrow(diamonds), 1e4)
mid <- interpret(price ~ (carat + cut + color + clarity)^2, diamonds[idx, ])
#> 'model' not passed: response variable in 'data' is used

# Plot a quantitative main effect
ggmid(mid, "carat")


# Plot a qualitative main effect
ggmid(mid, "clarity")


# Plot an interaction effect with data points and a raster layer
ggmid(mid, "carat:clarity", type = "compound", data = diamonds[idx, ])


# Use a different color theme
ggmid(mid, "clarity:color", theme = "RdBu")