Check the data's distribution. If non-normal, take the non-parametric variant of ggbetweenstats. x and y have to be in parentheses, e.g., "ConditionID".

Check the data's distribution. If non-normal, take the non-parametric variant of ggbetweenstats. x and y have to be in parentheses, e.g., "ConditionID".

Usage

ggbetweenstatsWithPriorNormalityCheck(
  data,
  x,
  y,
  ylab,
  xlabels = NULL,
  showPairwiseComp = TRUE,
  plotType = "boxviolin"
)

plot_between_stats(
  data,
  x,
  y,
  ylab,
  xlabels = NULL,
  showPairwiseComp = TRUE,
  plotType = "boxviolin"
)

Arguments

data

the data frame

x

the independent variable, most likely "ConditionID"

y

the dependent variable under investigation

ylab

label to be shown for the dependent variable

xlabels

labels to be used for the x-axis

showPairwiseComp

whether to show pairwise comparisons, TRUE as default

plotType

either "box", "violin", or "boxviolin" (default)

Value

A ggplot object produced by ggstatsplot::ggbetweenstats, which can be printed or further modified with +.

Naming

plot_between_stats() is the spelling used throughout the documentation and the one to prefer in new code: the report_* / plot_* / check_* prefixes make the API discoverable through autocomplete.

ggbetweenstatsWithPriorNormalityCheck() is the original name. Both names refer to the same function object, so they are entirely interchangeable; the original remains fully supported and is not scheduled for removal, and existing scripts keep working unchanged.

Examples

# \donttest{

set.seed(123)

# Toy within-subject style data
main_df <- data.frame(
  Participant = factor(rep(1:20, each = 3)),
  CondID      = factor(rep(c("A", "B", "C"), times = 20)),
  tlx_mental  = rnorm(60, mean = 50, sd = 10)
)

# Custom x-axis labels
labels_xlab <- c("Condition A", "Condition B", "Condition C")


ggbetweenstatsWithPriorNormalityCheck(
  data = main_df,
  x = "CondID",
  y = "tlx_mental", ylab = "Mental Demand",
  xlabels = labels_xlab,
  showPairwiseComp = TRUE
)
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.

# }