Is the following methodology correct:
- Fit a multiple linear regression model
- Obtain the standardized coefficients
- Sum up the absolute value of all standardized coefficients
- Divide each individual standardized coefficient estimate by the sum (step 3 above) and multiply by 100 to obtain the % contribution of each predictor variable
If this is incorrect, what is the best way to determine the relative importance of each predictor? In reading other posts, I've found Kruskal's key driver analysis to be one suggestion.....