Visualize CLOSURE data in a barplot

Call closure_plot_bar() to get a barplot of CLOSURE results.

For each scale value, the bars show how often this value appears in the mean samples with the minimum or maximum horns index (\(h\)). This displays the typical sample with the least or most amount of variance from among all CLOSURE samples.

As CLOSURE finds all possible samples, this plot shows the min and max possible amount of variance given the input statistics.

Usage

closure_plot_bar(
  data,
  min_max = c("both", "min", "max"),
  format = c("percent", "absolute_percent", "absolute", "relative"),
  samples = c("mean", "all"),
  overlay = c("all_avg", "none", "interval", "pointinterval", "dots"),
  facet_labels = c("Minimal variance", "Maximal variance"),
  facet_labels_parens = "h",
  bar_alpha = 0.75,
  bar_color = "#5D3FD3",
  show_text = TRUE,
  text_color = bar_color,
  text_size = 12,
  text_offset = 0.05,
  mark_thousand = ",",
  mark_decimal = "."
)

Arguments

data

List returned by closure_generate() or closure_read().

min_max

String (length 1). Which plot panel(s) to show? Options are "both" (the default), "min", and "max".

format

String (length 1). What should the bars show? The default is "percent". Similarly, "absolute_percent" shows the count of each scale value and its percentage of all values. Other options are "absolute" and "relative" frequencies.

samples

String (length 1). How to aggregate the samples? Either take the average sample ("mean", the default) or the sum of all samples ("all"). This only matters if absolute frequencies are shown.

overlay

String (length 1). Visualization mode for the frequency distribution across all samples, overlaid behind the main bars. Only applies when samples = "mean". Options:

"all_avg" (default): gray background bars showing the mean frequency across all samples.
"none": no overlay.
"interval": nested quantile intervals via ggdist::stat_interval() (requires the ggdist package and include = "all" in closure_generate()).
"pointinterval": median point with quantile interval lines via ggdist::stat_pointinterval() (same requirements as "interval").
"dots": quantile dot plot via ggdist::stat_dots() (same requirements as "interval").

facet_labels

String (length 2). Labels of the two individual panels. Set it to NULL to remove the labels. Default is c("Minimal variance", "Maximal variance").

facet_labels_parens

String (length 1). Italicized part of the facet labels inside the parentheses. Set it to NULL to remove the parentheses altogether. See details. Default is "h".

bar_alpha

Numeric (length 1). Opacity of the bars. Default is 0.75.

bar_color

String (length 1). Color of the bars. Default is "#5D3FD3", a purple color.

show_text

Logical (length 1). Should the bars be labeled with the corresponding frequencies? Default is TRUE.

text_color

String (length 1). Color of the frequency labels. By default, the same as bar_color.

text_size

Numeric (length 1). Base font size in pt. Default is 12.

text_offset

Numeric (length 1). Distance between the text labels and the bars. Default is 0.05.

mark_thousand, mark_decimal

Strings (length 1 each). Delimiters between groups of digits in text labels. Defaults are "," for mark_thousand (e.g., "20,000") and "." for mark_decimal (e.g., "0.15").

Value

A ggplot object.

Details

By default, both faceted plots have a label that includes their horns index (\(h\)); see horns(). You can remove the parenthesized part using facet_labels_parens = NULL or the entire label using facet_labels = NULL.

Examples

# Create CLOSURE data first:
data <- closure_generate(
  mean = "2.9",
  sd = "0.5",
  n = 70,
  scale_min = 1,
  scale_max = 5
)
#> 
#> ✔ All CLOSURE results found

# Even with minimal and maximal variance,
# the results are almost the same:
closure_plot_bar(data)


# Only show the minimum-variance panel:
closure_plot_bar(data, min_max = "min")

Usage

Arguments

Value

Details

See also

Examples