Pie Charts — jjpiestats • jjstatsplot

'Wrapper Function for ggstatsplot::ggpiestats and ggstatsplot::grouped_ggpiestats to generate Pie Charts with statistical analysis.'

Usage

jjpiestats(
  data,
  dep,
  group = NULL,
  grvar = NULL,
  typestatistics = "parametric",
  originaltheme = FALSE,
  counts = NULL,
  ratio = "",
  paired = FALSE,
  label = "percentage",
  digits = 2,
  conflevel = 0.95,
  proportiontest = TRUE,
  bfmessage = TRUE,
  messages = FALSE,
  clinicalpreset = "custom",
  showexplanations = TRUE,
  resultssubtitle = FALSE
)

Arguments

data: The data as a data frame.
dep: The categorical variable to display in the pie chart. This variable will be used to create pie slices representing the proportion of each category. Must be a factor variable.
group: Optional grouping variable for creating contingency table analysis. When specified, creates a 2x2 or 2xN contingency table and performs association tests (Chi-square, Fisher's exact test, etc.).
grvar: Optional variable to create separate pie charts for each level of this grouping variable. Creates a panel of pie charts, one for each group level (e.g., separate charts by treatment center or study site).
typestatistics: Type of statistical test for categorical association analysis. 'parametric' uses Pearson's Chi-square test, 'nonparametric' uses contingency table tests, 'robust' uses robust association measures, 'bayes' provides Bayesian analysis with Bayes factors.
originaltheme: Whether to apply the original ggstatsplot theme layer to the plot. If TRUE, uses ggstatsplot's default styling. If FALSE, uses jamovi's default ggplot2 theme for consistency with other analyses.
counts: A variable in data containing counts, or NULL if each row represents a single observation. Use this when your data is already aggregated/tabulated.
ratio: A comma-separated list of expected proportions for the proportion test (should sum to 1). For example: '0.5,0.5' for two equal groups or '0.25,0.25,0.25,0.25' for four equal groups. Leave empty for equal theoretical proportions.
paired: Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE). If TRUE, McNemar's test will be used. If FALSE, Pearson's chi-square test will be used.
label: What information needs to be displayed on the label in each pie slice.
digits: Number of digits after decimal point for statistical results.
conflevel: Confidence/credible interval level.
proportiontest: Decides whether proportion test for x variable is to be carried out for each level of y.
bfmessage: Display Bayes Factor in favor of the null hypothesis. Only relevant for parametric test.
messages: Display statistical messages in console. Disabling improves performance.
clinicalpreset: Predefined configurations for common clinical scenarios. Automatically sets appropriate statistical methods and parameters.
showexplanations: Display detailed explanations of statistical methods, assumptions, and clinical interpretations to guide analysis and result interpretation.
resultssubtitle: Whether to display statistical test results as subtitle in the pie chart. Shows test statistics, p-values, effect sizes, and confidence intervals for categorical association tests. Provides detailed statistical summary.

Value

A results object containing:

`results$about`					a html
`results$summary`					a html
`results$assumptions`					a html
`results$interpretation`					a html
`results$report`					a html
`results$todo`					a html
`results$plot4`					an image
`results$plot2`					an image
`results$plot1`					an image

Examples

# \donttest{
# Load test data
data(jjpiestats_test_data)
#> Warning: data set ‘jjpiestats_test_data’ not found

# Basic pie chart
jjpiestats(
  data = jjpiestats_test_data,
  dep = "treatment_response",
  typestatistics = "parametric"
)
#> Error: object 'jjpiestats_test_data' not found

# Pie chart with grouping
jjpiestats(
  data = jjpiestats_test_data,
  dep = "treatment_response",
  group = "treatment_arm",
  resultssubtitle = TRUE
)
#> Error: object 'jjpiestats_test_data' not found

# Grouped pie charts by split variable
jjpiestats(
  data = jjpiestats_test_data,
  dep = "disease_severity",
  group = "gender",
  grvar = "hospital_site",
  typestatistics = "nonparametric"
)
#> Error: object 'jjpiestats_test_data' not found
# }