Hi,
I am running coldiag2 command to detect multicollinearity in my data. I understand that each condition index is the ratio of the square root of the largest eigenvalue divided by the corresponding eigenvalue in the row. However, I am having difficulty understanding the variance decomposition entries. You can find a sample code and output below:
sysuse auto.dta
coldiag2 weight length displacement trunk, noconstant
Here, each column sums up to 1. Since we are trying to understand how much a variable contributes to the variance of an estimated coefficient (betas), shouldn't we have rows sum up to 1 instead of columns? Can anyone explain what these numbers represent? I looked at the help file but couldn't find a detailed discussion. Thank you.
Ulas
I am running coldiag2 command to detect multicollinearity in my data. I understand that each condition index is the ratio of the square root of the largest eigenvalue divided by the corresponding eigenvalue in the row. However, I am having difficulty understanding the variance decomposition entries. You can find a sample code and output below:
sysuse auto.dta
coldiag2 weight length displacement trunk, noconstant
| Condition | number using scaled variables = 30.47 | |
| Condition | Indexes and Variance-Decomposition Proportions | |
| condition | ||
| index | weight length displacement trunk | |
| 1 1.00 | 0.00 0.00 0.00 0.00 | |
| 2 7.58 | 0.00 0.03 0.34 0.11 | |
| 3 11.44 | 0.02 0.12 0.02 0.89 | |
| 4 30.47 | 0.98 0.85 0.64 0.00 |
Here, each column sums up to 1. Since we are trying to understand how much a variable contributes to the variance of an estimated coefficient (betas), shouldn't we have rows sum up to 1 instead of columns? Can anyone explain what these numbers represent? I looked at the help file but couldn't find a detailed discussion. Thank you.
Ulas
