Several methods are used to detect multicollinearity. One common approach is to calculate the Variance Inflation Factor (VIF), which quantifies how much the variance of an estimated regression coefficient is increased due to multicollinearity. A VIF value greater than 10 is often considered indicative of high multicollinearity. Another method is examining the correlation matrix of the predictor variables; high correlations between pairs of variables suggest multicollinearity.
