mosaic: Plot the distribution of categorical covariates

In vecmatch: Generalized Propensity Score Estimation and Matching for Multiple Groups

Plot the distribution of categorical covariates

Description

The mosaic() function generates imbalance plots for contingency tables with up to three variables. Frequencies in the contingency table are represented as tiles (rectangles), with each tile's size proportional to the frequency of the corresponding group within the entire dataset. The x-axis scale remains fixed across mosaic plots, enabling straightforward comparisons of imbalance across treatment groups.

Usage

mosaic(
  data = NULL,
  y = NULL,
  group = NULL,
  facet = NULL,
  ncol = 1,
  group_counts = FALSE,
  group_counts_size = 4,
  significance = FALSE,
  plot_name = NULL,
  overwrite = FALSE,
  ...
)

Arguments

data	A non-empty data.frame containing at least one numeric column, as specified by the y argument. This argument must be provided and does not have a default value.
y	A single string or unquoted symbol representing the name of a numeric column in the data. In the vector matching workflow, it is typically a numeric covariate that requires balancing.
group	A single string or unquoted symbol representing the name of a factor or character column in data. In raincloud() plots, the groups specified by group argument will be distinguished by separate fill and color aesthetics. For clarity, it is recommended to plot fewer than 10 groups, though there is no formal limit.
facet	A single string or unquoted symbol representing the name of a variable in data to facet by. This argument is used in a call to ggplot2::facet_wrap(), creating separate distribution plots for each unique group in the facet variable.
ncol	A single integer. The value should be less than or equal to the number of unique categories in the facet variable. This argument is used only when facet is not NULL, specifying the number of columns in the ggplot2::facet_wrap() call. The distribution plots will be arranged into the number of columns defined by ncol.
group_counts	A logical flag. If TRUE, the sizes of the groups will be displayed inside the rectangles in the plot created by the mosaic() function. If FALSE (default), the group sizes will not be shown.
group_counts_size	A single numeric value that specifies the size of the group count labels in millimeters ('mm'). This value is passed to the size argument of ggplot2::geom_text().
significance	A logical flag; defaults to FALSE. When TRUE, a Chi-squared test of independence is performed on the contingency table of y and group. Note that group must be specified for the test to be calculated. If facet is provided, the significance is assessed separately for each facet subgroup. Additionally, the function calculates standardized Pearson residuals (differences between observed and expected counts) and fills mosaic plot cells based on the level of partial significance for each cell.
plot_name	A string specifying a valid file name or path for the plot. If set to NULL, the plot is displayed to the current graphical device but not saved locally. If a valid name with .png or .pdf extension is provided, the plot is saved locally. Users can also include a subdirectory in plot_name. Ensure the file path follows the correct syntax for your operating system.
overwrite	A logical flag (default FALSE) that is evaluated only if the save.name argument is provided. If TRUE, the function checks whether a plot with the same name already exists. If it does, the existing plot will be overwritten. If FALSE and a plot with the same name exists, an error is thrown. If no such plot exists, the plot is saved normally.
...	Additional arguments to pass to rstatix::chisq_test when significance = TRUE.

Value

A ggplot object representing the contingency table of y and group as a mosaic plot, optionally grouped by facet if specified.

Examples

## Example: Creating a Mosaic Plot of the Titanic Dataset
## This plot visualizes survival rates by gender across different passenger
## classes. By setting `significance = TRUE`, you can highlight statistically
## significant differences within each rectangle of the mosaic plot.
library(ggplot2)

# Load Titanic dataset and convert to data frame
titanic_df <- as.data.frame(Titanic)

# Expand the dataset by repeating rows according to 'Freq'
titanic_long <- titanic_df[rep(
  seq_len(nrow(titanic_df)),
  titanic_df$Freq
), ]

# Remove the 'Freq' column as it is no longer needed
titanic_long$Freq <- NULL

# Plot the data using mosaic() and modify the result using additional ggplot2
# functions
p <- vecmatch::mosaic(
  data = titanic_long,
  y = Survived,
  group = Sex,
  facet = Class,
  ncol = 2,
  significance = TRUE
)

p <- p +
  theme_minimal()

p

vecmatch documentation built on April 3, 2025, 8:46 p.m.