esci (version 1.0.7)

plot_describe: Plot a histogram or dotplot of an estimated magnitude with raw data

Description

plot_describe Takes an estimate produced from estimate_magnitude and produces a dotplot or histogram. It can mark various descriptive statistics on the plot, including mean, median, sd, quartiles, and z lines. If a percentile is passed, it color-codes data based on if it is above or below that percentile.

Usage

plot_describe(
  estimate,
  type = c("histogram", "dotplot"),
  mark_mean = FALSE,
  mark_median = FALSE,
  mark_sd = FALSE,
  mark_quartiles = FALSE,
  mark_z_lines = FALSE,
  mark_percentile = NULL,
  histogram_bins = 12,
  ylim = c(0, NA),
  ybreaks = NULL,
  xlim = c(NA, NA),
  xbreaks = NULL,
  fill_regular = "#008DF9",
  fill_highlighted = "#E20134",
  color = "black",
  marker_size = 5,
  ggtheme = NULL
)

Value

Returns a ggplot object

Arguments

estimate

A esci_estimate object with raw data an es_mean

type

histogram or dotplot

mark_mean

should mean be marked?

mark_median

should median be marked?

mark_sd

should mean be marked?

mark_quartiles

should mean be marked?

mark_z_lines

should z lines be marked?

mark_percentile

a percentile (0 to 1) to be marked

histogram_bins

number of bins if a histogram

ylim

2-length numeric vector

ybreaks

numeric >= 1

xlim

2-length numeric vector

xbreaks

numeric >= 1

fill_regular

color for

fill_highlighted

color for

color

outline color

marker_size

Size of markers

ggtheme

theme to apply, if any

Details

This function was developed primarily for student use within jamovi when learning along with the text book Introduction to the New Statistics, 2nd edition (Cumming & Calin-Jageman, 2024).

Expect breaking changes as this function is improved for general use. Work still do be done includes:

• Revise to avoid deprecated ggplot features

• Revise for consistent ability to control aesthetics and consistent layer names

Examples

# example code
# Generate an estimate on a single continuous variable
estimate <- esci::estimate_magnitude(esci::data_latimier_3groups, `Test%`)

# Now describe the result, with a histogram
myplot_hist <- plot_describe(estimate)

# Same, but as a dotplot and mark the mean
myplot_dots <- plot_describe(estimate, type = "dotplot", mark_mean = TRUE)