Raincloud Plot — raincloud • ClinicoPath

Creates Raincloud plots to visualize data distributions using ggdist package. Raincloud plots combine three visualization techniques: half-violin plots showing distribution density, box plots showing summary statistics, and dot plots showing individual data points. This provides a comprehensive view of data distribution that reveals patterns traditional box plots might miss, including multimodality and distribution shape. Based on the ggdist R-Bloggers tutorial.

Usage

raincloud(
  data,
  dep_var,
  group_var,
  facet_var = NULL,
  color_var = NULL,
  show_violin = TRUE,
  show_boxplot = TRUE,
  show_dots = TRUE,
  dots_side = "left",
  violin_width = 0.7,
  box_width = 0.2,
  dots_size = 1.2,
  alpha_violin = 0.7,
  alpha_dots = 0.8,
  orientation = "horizontal",
  color_palette = "clinical",
  plot_theme = "clinical",
  plot_title = "Raincloud Plot - Distribution Visualization",
  x_label = "",
  y_label = "",
  show_statistics = TRUE,
  show_outliers = FALSE,
  outlier_method = "iqr",
  normality_test = FALSE,
  comparison_test = FALSE,
  comparison_method = "auto"
)

Arguments

data: The data as a data frame.
dep_var: Continuous variable whose distribution will be visualized in the raincloud plot.
group_var: Categorical variable for grouping. Each group will have its own raincloud visualization.
facet_var: Optional variable for creating separate panels. Creates multiple raincloud plots in a grid layout.
color_var: Optional variable for coloring different elements. If not specified, uses grouping variable.
show_violin: If TRUE, displays half-violin plot showing probability density distribution.
show_boxplot: If TRUE, displays box plot with median, quartiles, and outliers.
show_dots: If TRUE, displays individual data points as dots.
dots_side: Position of data point dots relative to the violin plot.
violin_width: Width scaling factor for the violin plot component.
box_width: Width of the box plot component.
dots_size: Size of individual data point dots.
alpha_violin: Transparency level for violin plot (0 = transparent, 1 = opaque).
alpha_dots: Transparency level for data point dots.
orientation: Orientation of the plot. Horizontal creates the classic "raincloud" appearance.
color_palette: Color palette for different groups including GraphPad Prism palettes.
plot_theme: Overall visual theme for the plot.
plot_title: Custom title for the raincloud plot.
x_label: Custom label for X-axis. If empty, uses variable name.
y_label: Custom label for Y-axis. If empty, uses variable name.
show_statistics: If TRUE, displays summary statistics table for each group.
show_outliers: If TRUE, identifies and highlights outliers in the visualization.
outlier_method: Method for detecting outliers when highlight outliers is enabled.
normality_test: If TRUE, performs normality tests (Shapiro-Wilk) for each group.
comparison_test: If TRUE, performs statistical tests to compare groups.
comparison_method: Statistical test method for comparing groups.

Value

A results object containing:

`results$todo`					a html
`results$plot`					an image
`results$statistics`					a html
`results$outliers`					a html
`results$normality`					a html
`results$comparison`					a html
`results$interpretation`					a html

Examples

# Load example dataset
data(histopathology)

# Basic raincloud plot
raincloud(
  data = histopathology,
  dep_var = "Age",
  group_var = "Group"
)
#> Error in private$.analysis_data <- analysis_data: cannot add bindings to a locked environment

# Advanced raincloud plot with faceting and custom colors
raincloud(
  data = histopathology,
  dep_var = "OverallTime",
  group_var = "Group",
  facet_var = "Sex",
  color_var = "Race",
  color_palette = "clinical",
  plot_theme = "publication"
)
#> Error in private$.analysis_data <- analysis_data: cannot add bindings to a locked environment

# Statistical analysis with outlier detection
raincloud(
  data = histopathology,
  dep_var = "Age",
  group_var = "Group",
  show_statistics = TRUE,
  show_outliers = TRUE,
  outlier_method = "iqr",
  normality_test = TRUE,
  comparison_test = TRUE
)
#> Error in private$.analysis_data <- analysis_data: cannot add bindings to a locked environment

# Customized visualization components
raincloud(
  data = histopathology,
  dep_var = "Age",
  group_var = "Group",
  show_violin = TRUE,
  show_boxplot = TRUE,
  show_dots = TRUE,
  dots_side = "left",
  orientation = "horizontal",
  violin_width = 0.8,
  alpha_violin = 0.6
)
#> Error in private$.analysis_data <- analysis_data: cannot add bindings to a locked environment