I am using a logistic regression and my biggest problem is the very low correlations between the dependent and independents. The highest correlation with the dependent variable is a spend variable with a boxcox transformation and yield only a correlation of 0.2.
The results of my model are not very impressive and this, I beleive, it is related to the fact that all of the variables have a correlation lower or equal to 0.2 with the dependent,
the area under the curve is 0.684 and the classification table is below. on final note, I did try different transformations on all independents and interactions as well.
Did someone had a similar experience?
I can't recall if this ever happened to me, but low correlations usually mean poor model fit
After my posting, I have added a new variable from the database to my list of predictors and the distribution was bimodal which led me to think that my sample is including two different kind of population, i have corrected this and correlations are now fine
This is a super good example of how important data visualization is to good analysis.
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