plot_mean_response_1D: Plot mean of a response variable across a single variable,...

In MAPCtools: Multivariate Age-Period-Cohort (MAPC) Modeling for Health Data

Plot mean of a response variable across a single variable, optionally stratified

Description

Computes the mean of a specified response variable at each value of a specified x variable and displays a line plot using ggplot2. If a stratification variable is provided, means are calculated per strata and plotted as separate colored lines. If an additional stratification variable is provided, separate plot windows are created for each level.

Usage

plot_mean_response_1D(
  data,
  response,
  x,
  stratify_by = NULL,
  for_each = NULL,
  title = NULL,
  subtitle = NULL,
  legend_title = NULL,
  x_lab = NULL,
  y_lab = NULL,
  viridis_color_option = "D"
)

Arguments

data	A data.frame or tibble containing the dataset.
response	A numeric variable in data whose mean will be plotted.
x	A variable in data defining the x-axis for computing means.
stratify_by	(Optional) Stratification variable. If supplied, counts are computed for each combination of x and stratify_by, and separate lines are drawn per level of stratify_by.
for_each	(Optional) Additional stratification variable. If supplied, separate plot windows are created per level of for_each.
title	(Optional) Plot title; defaults to "Observation counts".
subtitle	(Optional) Plot subtitle; defaults to NULL if for for_each is NULL, defaults to <name of for_each>: <level of for_each> for each plot window if for_each is supplied.
legend_title	(Optional) Legend title; defaults to name of stratify_var if it is supplied.
x_lab	(Optional) Label for the x-axis; defaults to the name of x.
y_lab	(Optional) Label for the y-axis; defaults to the name of paste("Mean", <response_name>).
viridis_color_option	(Optional) Option for color gradient; defaults to "D". Options are "A", "B", "C", "D", E", "F", "G", "H". See viridis for information, or experiment yourself.

Value

A ggplot object displaying the mean of the response across the variable supplied in x, optionally stratified by stratify_by. If for_each is supplied, separate plots are created in separate windows for each level. Visuals can be modified with ggplot2.

See Also

plot_mean_response_2D, ggplot

Examples

data("toy_data")
# Mean by age
plot_mean_response_1D(toy_data, response = count, x = age)
# Mean count by age, stratified by education
plot_mean_response_1D(toy_data, response = count, x = age,
                      stratify_by = education)
# Mean count by age, stratified by education, for each sex
plot_mean_response_1D(toy_data, response = count, x = age,
                      stratify_by = education, for_each = sex)

MAPCtools documentation built on June 25, 2025, 5:09 p.m.