Plot non-directional mixed-type pairwise mining matrices

Builds referent-centred phenotype screening matrices that show the magnitude of pairwise separation only. Signed continuous contrasts and category-level prevalence contrasts are retained in returned audit objects for follow-up, but are deliberately not displayed in the mining matrices.

Usage

PlotPairwiseMiningMatrix(
  data,
  group_var,
  variables,
  Referent,
  covariates = NULL,
  adjust_scope = c("per_group", "per_variable", "matrix", "none"),
  p_adjust_method = c("fdr", "bonferroni", "holm", "none"),
  star_p = c("raw", "adjusted", "none"),
  adjusted_outline = TRUE,
  adjusted_significance_threshold = 0.05,
  adjusted_outline_color = "black",
  adjusted_outline_linewidth = 1,
  variable_metadata = NULL,
  max_levels = 30,
  continuous_fill_limits = NULL,
  categorical_fill_limits = NULL,
  x_axis_text_angle = 0,
  row_label_width = 58
)

Arguments

data

A data frame with labelled variables.

group_var

Character scalar naming the grouping variable.

variables

Character vector of continuous or categorical variables.

Referent

Character scalar naming the referent level of group_var.

covariates

Optional character vector of covariates. Continuous contrasts use these covariates; Cramer's V screening remains unadjusted.

adjust_scope

Multiple-comparison correction scope: "per_group", "per_variable", "matrix", or "none".

p_adjust_method

Method passed to stats::p.adjust().

star_p

Which p-values drive cell stars: "raw", "adjusted", or "none".

adjusted_outline

Logical; outline cells significant after adjustment.

adjusted_significance_threshold

Threshold for adjusted-significant outlines.

adjusted_outline_color, adjusted_outline_linewidth

Appearance of the adjusted-significant outline.

variable_metadata

Optional data frame with Variable and optional AnchorN, AlignedN, FilledPrior, FilledFuture, and TimeExtended.

max_levels

Maximum categorical levels allowed for one variable.

continuous_fill_limits, categorical_fill_limits

Optional non-negative plotting limits for the continuous and categorical magnitude matrices.

x_axis_text_angle

Numeric angle for phenotype labels.

row_label_width

Approximate character width used to wrap row labels.

Value

An object of class "SciDataReportRPairwiseMiningMatrix" with Plots, Results, ContinuousAudit, CategoryLevelResults, Settings, Models, and Warnings. Plots$Continuous displays absolute referent-SD mean differences and Plots$Categorical displays pairwise Cramer's V. Both use an independent pale-gray-to-navy magnitude scale.

Details

The required Referent determines the phenotype comparison columns. Continuous cells are absolute Group - Referent contrasts in reference-SD units. Categorical cells are pairwise Cramer's V values from contingency tables, one row per variable. These metrics intentionally have separate legends and should not be compared as interchangeable effect sizes.