Hi All,
I am running logistic regression model using variable selection, variable transform with maximum normal and then again variables transform with optimal binning.
I am getting quite good roc index and miss-classification rate.
In the effects plot I have many variables in blue (i guess that means positive effect) and one variable with red column (negative effect).
but in the Analysis of Maximum Likelihood Estimates many variables are negative and only one is positive i.e. exactly the opposite of the effect plot.
How to explain this?
Thank you!
Analysis of Maximum Likelihood Estimates
Standard Wald
Parameter DF Estimate Error Chi-Square Pr > ChiSq Exp(Est)
OPT_Age 01:low-34.5 1 -1.1347 0.3570 10.10 0.0015 0.322
OPT_BMI 01:low-28.540152 1 -0.9561 0.3507 7.43 0.0064 0.384
OPT_FG 01:low-99.5, MISSING 1 -0.3387 0.3248 1.09 0.2971 0.713
OPT_HDL 01:low-45.4 1 0.9830 0.3946 6.21 0.0127 2.672
OPT_LDL 01:low-114.3, MISSING 1 -0.5588 0.4448 1.58 0.2091 0.572
OPT_Ratio_New 01:low-0.6322109, MISSING 1 -0.7628 0.3756 4.12 0.0423 0.466
OPT_TC 01:low-201.25, MISSING 1 -0.1096 0.5006 0.05 0.8267 0.896
OPT_Tryg 01:low-190.2, MISSING 1 -0.1636 0.3848 0.18 0.6706 0.849
Hi I have a quick answer for you. If you look at the legend below the chart, red is positive and blue is negative. That matches your Parameter Estimates.
Thanks,
Jonathan
Thank you Jonathan!
So, the moral is: always look to the legend 🙂
regards,
Gio
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