Correlation Matrix

# FALLBACK
library(dplyr)
if(!exists("raw_data")) {
   raw_data <- data.frame(
    age = rnorm(50, 20, 2),
    anxiety = rnorm(50, 10, 3),
    depression = rnorm(50, 10, 3)
  )
}

# 1. Select Numeric Vars
numeric_vars <- raw_data %>% 
  select(where(is.numeric)) 

# 2. Compute Correlation
cor_mat <- cor(numeric_vars, use = "complete.obs")

# 3. Simple Visualization (Round to 2 decimals)
round(cor_mat, 2) %>% 
  knitr::kable(caption = "Pearson Correlations")

Table 1: Correlation Matrix

Pearson Correlations

	age	anxiety	depression
age	1.00	-0.12	-0.14
anxiety	-0.12	1.00	-0.25
depression	-0.14	-0.25	1.00