Plot & Summarize Group Stats via MakeComparisonTable (BH q from p; SHAPE by p; COLOR by Category (vector or data frame); stable point size; palette via paletteer)

Usage

Plot2GroupStats(
  Data,
  Variables,
  VariableCategories = NULL,
  impClust,
  normalClust,
  GroupVar,
  missing_threshold = 0.8,
  max_levels = 10,
  label_q = 0.05,
  x_axis = c("signed_logp", "signed_effect", "effect", "logp"),
  sort_by = c("q", "p", "effect", "signed_logp", "signed_effect", "none"),
  mct_args = list(),
  palette = "pals::alphabet",
  point_size = 3.5
)

Arguments

Data: data.frame
Variables: character vector of variables to analyze
VariableCategories: optional: - data frame with columns Variable, Category; OR - vector of categories (named by variable OR unnamed aligned to Variables)
impClust, normalClust: labels for the two groups (impClust plotted to the RIGHT for signed axes)
GroupVar: column name in Data holding the group labels
missing_threshold: drop vars with > this fraction missing (default 0.80)
max_levels: drop factors with > this many levels (default 10)
label_q: label threshold using q (default 0.05)
x_axis: one of c("signed_logp","signed_effect","effect","logp")
sort_by: one of c("q","p","effect","signed_logp","signed_effect","none")
mct_args: list of extra args to SciDataReportR::MakeComparisonTable(); e.g., AddEffectSize=TRUE
palette: paletteer palette string for category colors (default "pals::alphabet")
point_size: numeric constant for point size (default 3.5)

Value

list(plot=ggplot, table=gtsummary, pvaltable=data.frame, data_used=tibble)