mccount (version 0.1.1)

plot.mcc: Plot MCC results

Description

Creates plots for Mean Cumulative Count (MCC) results. The plotting method automatically adapts based on the mcc object class and whether the analysis was grouped.

Usage

# S3 method for mcc
plot(
  x,
  type = c("mcc", "components"),
  groups = NULL,
  conf_int = FALSE,
  colors = NULL,
  title = NULL,
  subtitle = NULL,
  ...
)

Value

A ggplot2 object

Arguments

x

An mcc object

type

Character string specifying plot type:

• "mcc" (default): Plot MCC estimates over time

• "components": Show individual cumulative incidence components (SCI method only)

groups

Character vector specifying which groups to include in grouped analyses. If NULL (default), all groups are included

conf_int

Logical indicating whether to include confidence intervals if available

colors

Character vector of colors to use for groups. If NULL, uses default colors

title

Character string for plot title. If NULL, generates automatic title

subtitle

Character string for plot subtitle. If NULL, generates automatic subtitle

...

Additional arguments passed to ggplot2 functions

Examples

# Create sample data
library(dplyr)
df <- data.frame(
  id = c(1, 2, 3, 4, 4, 4, 4, 5, 5),
  time = c(8, 1, 5, 2, 6, 7, 8, 3, 3),
  cause = c(0, 0, 2, 1, 1, 1, 0, 1, 2),
  group = c("A", "A", "B", "B", "B", "B", "B", "A", "A")
) |>
  arrange(id, time)

# Basic MCC plot (ungrouped)
mcc_result <- mcc(df, "id", "time", "cause")
plot(mcc_result)

# Grouped analysis with custom colors
mcc_grouped <- mcc(df, "id", "time", "cause", by = "group")
plot(mcc_grouped)

# Customize the grouped plot
plot(mcc_grouped,
     colors = c("red", "blue"),
     title = "MCC by Treatment Group",
     subtitle = "Comparison of Event Burden")

# Plot only specific groups
plot(mcc_grouped, groups = c("A"))

# Compare different methods - equation method only shows MCC
mcc_eq <- mcc(df, "id", "time", "cause", method = "equation")
plot(mcc_eq)

# SCI method can show components of cumulative incidence components
mcc_sci <- mcc(df, "id", "time", "cause", method = "sci")
plot(mcc_sci)  # Shows main MCC plot
plot(mcc_sci, type = "components")  # Shows CI components

# Clean up
rm(df, mcc_result, mcc_grouped, mcc_eq, mcc_sci)