biostats (version 1.1.1)

plot_corr: Create Simple Professional Correlation Matrix Plots

Description

Generates publication-ready correlation matrix heatmaps with minimal code using ggplot2.

Usage

plot_corr(
  data,
  vars = NULL,
  method = c("pearson", "spearman"),
  type = c("full", "upper", "lower"),
  colors = NULL,
  title = NULL,
  show_values = TRUE,
  value_size = 3,
  show_sig = FALSE,
  sig_level = 0.05,
  sig_only = FALSE,
  show_legend = TRUE,
  p_method = "holm"
)

Value

A ggplot2 object

Arguments

data

A dataframe containing the variables to analyze.

vars

Character vector specifying which variables to include. Default: NULL.

method

Character string specifying correlation method: "pearson" or "spearman". Default: "pearson".

type

Character string specifying matrix type: "full", "upper", or "lower". Default: "full".

colors

Character vector of 3 colors for negative, neutral, and positive correlations. Default: NULL.

title

Character string for plot title. Default: NULL.

show_values

Logical parameter indicating whether to display correlation values in cells. Default: TRUE.

value_size

Numeric value indicating size of correlation value text. Default: 3.

show_sig

Logical parameter indicating whether to mark significant correlations. Default: FALSE.

sig_level

Numeric value indicating significance level for marking. Default: 0.05.

sig_only

Logical parameter indicating whether to show only statistically significant values. Default: FALSE.

show_legend

Logical parameter indicating whether to show legend. Default: TRUE.

p_method

Character string specifying the method for p-value adjustment to control for multiple comparisons in correlation testing. Options: "holm" (Holm), "hochberg" (Hochberg), "hommel" (Hommel), "bonferroni" (Bonferroni), "BH" (Benjamini-Hochberg), "BY" (Benjamini-Yekutieli), or "none" (no adjustment). Default: "holm".

Examples

# Correlation matrix for base R dataset 'swiss'
plot_corr(data = swiss)

# Lower triangle with significance indicators and filtering
plot_corr(data = swiss, type = "lower", show_sig = TRUE, sig_only = TRUE)