Hi All,
I was building a logistic regression, and part of the Odds Ratio result is shown below..
Odds Ratio Estimates |
Point |
Effect Estimate |
var_Finance_Insurance 0 vs NoCC 1.729 |
var_Finance_Insurance 1 vs NoCC 2.334 |
var_Gender F vs M 1.128 |
var_Health_GeneralHealth 0 vs NoCC 0.586 |
var_Health_GeneralHealth 1 vs NoCC . |
var_Leisure_BookWorm 0 vs NoCC 1.304 |
var_Leisure_BookWorm 1 vs NoCC . |
I am just wondering for var_Health_GeneralHealth (1 vs NoCC) and var_Leisure_Bookworm (1 vs NoCC), why does it have a Odd ratio of "."?
Is it because it has a same % as var_Finance_insurance for the NoCC? Below are my distribution for var_Health_General, var_Leisure_Bookworm and var_Finance_insurance.
var_Leisure_BookWorm | Count(*) | Sum(TARGET) | % |
1 | 4163 | 1068 | 0.25654576 |
0 | 25451 | 6239 | 0.245137716 |
NoCC | 16142 | 2993 | 0.185416925 |
var_Finance_Insurance | Count(*) | Sum(TARGET) | % |
1 | 9910 | 2872 | 0.289808274 |
0 | 19704 | 4435 | 0.225081202 |
NoCC | 16142 | 2993 | 0.185416925 |
var_Health_GeneralHealth | Count(*) | Sum(TARGET) | % |
1 | 4792 | 1502 | 0.313439065 |
0 | 24822 | 5805 | 0.23386512 |
NoCC | 16142 | 2993 | 0.185416925 |
If you are using GLM effect coding of your class inputs, then you will always have 1 level that has a missing estimate since the estimates are calculated in reference to one of the levels (the reference level) and the parameterization is singular. If you are using the Regression node in SAS Enterprise Miner, you can change the Input Coding property to Deviation to get estimates for all levels compared to the average effect of all levels.
Hi,
The result i shown was actually based on "Deviation" setting. I tried GLM as well, same thing happen. I am using EM12.1
Ahhh, ok. Then as you first said, I would think there is another input or coded effect perfectly correlated with the coded effect for the levels of those inputs.
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