plot_profile: Profile plot (spaghetti plot) for longitudinal data

In antedep: Antedependence Models for Longitudinal Data

Profile plot (spaghetti plot) for longitudinal data

Description

Creates a profile plot showing individual subject trajectories with overlaid mean trajectory and standard deviation bands.

Usage

plot_profile(
  y,
  time_points = NULL,
  blocks = NULL,
  block_labels = NULL,
  title = "Profile Plot",
  xlab = "Time",
  ylab = "Measurement",
  ylim = NULL,
  show_sd = TRUE,
  individual_alpha = 0.3,
  individual_color = "grey50",
  mean_color = "blue",
  sd_color = "red",
  mean_lwd = 2
)

Arguments

y	Numeric matrix with n_subjects rows and n_time columns, or a data frame with measurements.
time_points	Optional numeric vector of time points for x-axis. Default uses 1:n_time or attempts to extract from column names.
blocks	Optional integer vector of block memberships for stratified plotting. If provided, creates separate panels for each block.
block_labels	Optional character vector of labels for blocks.
title	Plot title. Default "Profile Plot".
xlab	X-axis label. Default "Time".
ylab	Y-axis label. Default "Measurement".
ylim	Optional y-axis limits as c(min, max).
show_sd	Logical; if TRUE (default), show +/- 1 SD error bars.
individual_alpha	Alpha (transparency) for individual trajectories. Default 0.3.
individual_color	Color for individual trajectories. Default "grey50".
mean_color	Color for mean trajectory. Default "blue".
sd_color	Color for SD error bars. Default "red".
mean_lwd	Line width for mean trajectory. Default 2.

Details

This function provides a quick visual summary of longitudinal data showing:

• Individual subject trajectories (light grey lines)

• Mean trajectory across subjects (bold colored line)

• +/- 1 standard deviation bands (error bars)

When blocks is provided, the plot is faceted by block membership, allowing comparison of trajectories across treatment groups or other strata.

Value

A ggplot2 object (invisibly). Called primarily for side effect (plotting).

Examples

data("bolus_inad")

# Basic profile plot
plot_profile(bolus_inad$y)

# With block stratification
plot_profile(bolus_inad$y, blocks = bolus_inad$blocks,
             block_labels = c("2mg", "1mg"))

# Customized
plot_profile(bolus_inad$y,
             time_points = seq(0, 44, by = 4),
             title = "Bolus Counts Over Time",
             xlab = "Hours", ylab = "Count")

antedep documentation built on April 25, 2026, 1:06 a.m.