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Plots for comparing categorical outcome variables between conditions

Source: R/plot_mdiff.R
plot_pdiff.Rd

plot_pdiff helps visualize comparisons of a categorical outcome variable between conditions. It plots proportions of cases for each level of grouping variable and emphasizes a 1-df comparison among conditions, plotting the estimated difference and its confidence interval with a difference axis. You can pass esci-estimate objects generated by estimate_pdiff_one(), estimate_pdiff_two(), estimate_pdiff_paired(), estimate_pdiff_ind_contrast() This function returns a ggplot2 object.

Usage

plot_pdiff(
  estimate,
  error_layout = c("halfeye", "eye", "gradient", "none"),
  error_scale = 0.3,
  error_normalize = c("groups", "all", "panels"),
  difference_axis_breaks = 5,
  difference_axis_space = 1,
  simple_contrast_labels = TRUE,
  ylim = c(NA, NA),
  ybreaks = 5,
  rope = c(NA, NA),
  ggtheme = NULL
)

Arguments

estimate

An esci-estimate object generated by an estimate_pdiff_ function

error_layout

Optional; one of 'halfeye', 'eye', 'gradient' or 'none' to determine how expected error distribution will be displayed for each estimated parameter. Defaults to 'halfeye'. Currently does not apply if 'median' is selected as effect size, in which case a simple error bar will be used

error_scale

Optional numeric determining width of the expected error distribution. Defaults to 0.3

error_normalize

Optional; one of 'groups', 'all', or 'panels' to determine how width of the expected error distributions will be normalized. Defaults to 'groups'. See documentation in ggdist

difference_axis_breaks

Optional numeric > 1 of suggested number of breaks for the difference axis. Defaults to 5

difference_axis_space

Optional numeric > 0 to indicate spacing to the difference axis. Defaults to 1

simple_contrast_labels

Optional logical to determine if contrasts are given simple labels ('Reference', 'Comparison', 'Difference') or more descriptive labels based on the contrast specified.

ylim

Optional 2-item vector specifying y-axis limits. Defaults to c(NA NA); Use NA to specify auto-limit.

ybreaks

Optional numeric > 2 for suggested number of y-axis breaks; defaults to 5

rope

Optional 2-item vector with item 2 >= item 1. Use to specify a range of values to use to visualize a hypothesis test. If both values are the same, a point-null hypothesis test will be visualized. If item2 > item1 an interval-null hypothesis test will be visualized. Defaults to c(NA, NA), which is to not visualize a hypothesis test

ggtheme

Optional ggplot2 theme object to specify the visual style of the plot. Defaults to ggplot2::theme_classic()

Value

Returns a ggplot object

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

data("data_campus_involvement")

estimate_from_raw <- esci::estimate_pdiff_two(
  esci::data_campus_involvement,
  CommuterStatus,
  Gender
)

# To visualize the estimate
myplot_from_raw <- esci::plot_pdiff(estimate_from_raw)
#> Warning: Using size for a discrete variable is not advised.
#> Warning: Using alpha for a discrete variable is not advised.
#> Warning: Using size for a discrete variable is not advised.
#> Warning: Using alpha for a discrete variable is not advised.

# To conduct a hypothesis test
res_htest_from_raw <- esci::test_pdiff(estimate_from_raw)


# From summary_data
estimate_from_summary <- esci::estimate_pdiff_two(
  comparison_cases = 10,
  comparison_n = 20,
  reference_cases = 78,
  reference_n = 252,
  grouping_variable_levels = c("Original", "Replication"),
  conf_level = 0.95
)

# To visualize the estimate
myplot_from_summary <- esci::plot_pdiff(estimate_from_summary)
#> Warning: Using size for a discrete variable is not advised.
#> Warning: Using alpha for a discrete variable is not advised.
#> Warning: Using size for a discrete variable is not advised.
#> Warning: Using alpha for a discrete variable is not advised.

#' # To conduct a hypothesis test
res_htest_from_summary <- esci::test_pdiff(estimate_from_summary)