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

In rcalinjageman/esci: Estimation Statistics with Confidence Intervals

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
)

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

Value

Returns a ggplot object

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)

rcalinjageman/esci documentation built on Dec. 23, 2024, 2:37 p.m.