mosaic_plot: Mosaic plot

In maraca: The Maraca Plot: Visualizing Hierarchical Composite Endpoints

Mosaic plot

Description

Generic function to create a mosaic plot that compares outcomes between an active treatment group and a control group, highlighting areas of "Wins", "Losses" and "Ties" based on endpoint hierarchy.

Usage

mosaic_plot(x, ...)

## Default S3 method:
mosaic_plot(x, ...)

## S3 method for class 'maraca'
mosaic_plot(
  x,
  theme = "maraca",
  highlight_ties = FALSE,
  win_prob = FALSE,
  diagonal_line = TRUE,
  ...
)

## S3 method for class 'adhce'
mosaic_plot(
  x,
  step_outcomes = NULL,
  last_outcome = "C",
  arm_levels = c(active = "A", control = "P"),
  theme = "maraca",
  highlight_ties = FALSE,
  win_prob = FALSE,
  diagonal_line = TRUE,
  lowerBetter = FALSE,
  ...
)

Arguments

x	an object of S3 class 'maraca' or 'adhce'.
...	not used
theme	Choose theme to style the plot. The default theme is "maraca". Options are "maraca", "color1", "color2" and "none". For more details, check the vignette called "Maraca Plots - Introduction to the Mosaic plot".
highlight_ties	Flag to indicate if component ties should be highlighted using lighter colors. Default value: FALSE
win_prob	Flag to indicate if winning probability should be shown within the plot. Note that in order to display the winning probability, you need to have set the "compute_win_odds" to TRUE when creating the maraca object. Default value: FALSE
diagonal_line	Flag to indicate if diagonal line showing an even Win/Loss split should be displayed. Default value: TRUE
step_outcomes	A vector of strings containing the outcome labels for all outcomes displayed as part of the step function on the left side of the plot. The order is kept for the plot. By default (when set to NULL) this is automatically updated by taking the non-continuous outcomes from the GROUP variable in alphabetical order.
last_outcome	A single string containing the last outcome label displayed on the right side of the plot. Default value "C".
arm_levels	A named vector of exactly two strings, mapping the values used for the active and control arms to the values used in the data. The names must be "active" and "control" in this order. Note that this parameter only need to be specified if you have labels different from "active" and "control".
lowerBetter	Flag for the final outcome variable, indicating if lower values are considered better/advantageous. This flag is need to make sure the win odds are calculated correctly. Default value is FALSE, meaning higher values are considered advantageous.

Details

Implemented for objects of type 'maraca' and 'adhce'.

Check the vignette "Maraca Plots - Introduction to the Mosaic plot" for more details.

Value

Mosaic plot as a ggplot2 object.

Examples

data(hce_scenario_a)

maraca_dat <- maraca(data = hce_scenario_a,
                     step_outcomes = c("Outcome I", "Outcome II",
                                      "Outcome III", "Outcome IV"),
                     last_outcome = "Continuous outcome",
                     fixed_followup_days = 3 * 365,
                     column_names = c(outcome = "GROUP",
                                      arm = "TRTP",
                                      value = "AVAL0"),
                     arm_levels = c(active = "Active",
                                    control = "Control"),
                     compute_win_odds = TRUE
                     )

mosaic_plot(maraca_dat)

Rates_A <- c(1.72, 1.74, 0.58, 1.5, 1)
Rates_P <- c(2.47, 2.24, 2.9, 4, 6)
hce_dat <- hce::simHCE(n = 2500, TTE_A = Rates_A, TTE_P = Rates_P,
             CM_A = -3, CM_P = -6, CSD_A = 16, CSD_P = 15, fixedfy = 3,
             seed = 31337)

mosaic_plot(hce_dat)

maraca documentation built on Nov. 21, 2025, 1:07 a.m.