Results of correlations, Anova and t-test

options(scipen=999)
correlation <- correlation_test$estimate
rounded_correlation <- round(correlation, 2)
df_degrees_of_freedom <- correlation_test$parameter
p_value <- correlation_test$p.value
rounded_p_value <- round(p_value, 4)
p_value <- correlation_test$p.value
cat(sprintf("Degrees of freedom: %d\n", df_degrees_of_freedom))
cat(sprintf("P-value: %.4f\n", p_value))
cat(sprintf("Correlation: %.2f\n", rounded_correlation))
cat(sprintf("The correlation between `SUD_post` and `SUD_followup` is %.2f with %d degrees of freedom and a p-value of %.4f.", cor_coeff, df_degrees, p_value))

Correlations

The results of the correlation analysis showed a non-significant, strong positive correlation between “SUD_post” and “SUD_followup” scores,r (155), = 0.4456463, p = 0.