While covariance matrices are powerful, other methods can sometimes be more appropriate:
Correlation Matrix: Standardizes the covariance matrix by using the correlation coefficients, which are unitless and easier to interpret. Partial Correlation: Measures the relationship between two variables while controlling for the effect of other variables. Generalized Estimating Equations (GEE): Useful for repeated measures or clustered data, providing a way to account for within-subject correlations.
