I've got a Logistic model built for a particular response-non response event.
The model suggests statistics that don't look like a robust model. I'm sharing those for more clarification..
No. of variables - around 5-8
c = 0.9
concordance = 0.93
H-L Chi square (Goodness of Fit)= 700 (P 0.0001) (rejects Null - bad model characteristics)
Also, a univariate distribution of P(Y=1|X1..Xn) gives me 95% of the probabilities fall within 0.4!!! Which suggests that the model does poorer than a random!!
What are the ways to improve my model? I know of one or two methods that I surfed through recently, but none hands on.. Would like to hear any advice on this!
Thanks in advance.