Plot Numerical Interaction Effects Matrix

This function calculates interaction effects between numerical variables and plots them as matrices.

Usage

PlotNumInteractionEffectsMatrix(
  data,
  predictor_vars,
  outcome_vars = NULL,
  xVarLabels = NULL,
  yVarLabels = NULL,
  interVar = NULL,
  covariates = NULL,
  Data = lifecycle::deprecated(),
  xVars = lifecycle::deprecated(),
  yVars = lifecycle::deprecated(),
  fdr_scope = c("matrix", "per_outcome", "per_predictor"),
  covars = lifecycle::deprecated()
)

Arguments

data

The dataset containing the variables.

predictor_vars

A character vector of the names of the x-axis numerical variables.

outcome_vars

A character vector of the names of the y-axis numerical variables. Defaults to NULL.

xVarLabels

A character vector of labels for the x-axis variables. Defaults to NULL.

yVarLabels

A character vector of labels for the y-axis variables. Defaults to NULL.

interVar

The interaction variable. Defaults to NULL.

covariates

A character vector of the names of covariate variables. Defaults to NULL.

Data

Deprecated (since 19.15.0). Use data instead.

xVars

Deprecated (since 19.15.0). Use predictor_vars instead.

yVars

Deprecated (since 19.15.0). Use outcome_vars instead.

fdr_scope

Either "matrix" (default) or "per_outcome", passed to ApplyFDRCorrection(). "matrix" corrects across all interaction p-values at once (historical behavior). "per_outcome" corrects separately within each y-axis variable (outcome_vars).

covars

Deprecated (since 19.15.0). Use covariates instead.

Value

A list containing matrices, ggplot objects for visualizations, and tables of p-values.

Examples

data(SampleData)
data(SampleVariableTypes)

# Attach labels and factor levels for readable axes
Labelled <- RevalueData(SampleData, SampleVariableTypes)$RevaluedData

result <- PlotNumInteractionEffectsMatrix(
  Labelled,
  predictor_vars = c("Alpha_2_Macroglobulin", "Angiopoietin_2_ANG_2",
                     "Apolipoprotein_A_IV", "Apolipoprotein_A1",
                     "Apolipoprotein_A2", "Apolipoprotein_B",
                     "Apolipoprotein_CI", "Apolipoprotein_CIII",
                     "Apolipoprotein_D", "Apolipoprotein_E"),
  outcome_vars = c("ACE_CD143_Angiotensin_Converti",
                   "ACTH_Adrenocorticotropic_Hormon", "AXL", "Adiponectin",
                   "Alpha_1_Antichymotrypsin", "Alpha_1_Antitrypsin",
                   "Alpha_1_Microglobulin"),
  interVar = "age"
)
#> Joining with `by = join_by(X, Y)`
#> Joining with `by = join_by(X, Y)`

# Raw p-value interaction matrix
result$p


# FDR-adjusted interaction matrix
result$p_FDR