logistic regression : intercept is NOT significative

#1
Hi everybody

I have performed a logistic regression with a stepwise selection. But, at the end, the parameter estimate of intercept is NOT significative.

What should I do ?

Thanks for the help
 

WeeG

TS Contributor
#2
I am not sure there is much you can do, usually it's not advisable to remove the intercept, even when it's not significantly different than 0, since it can make your prediction biased. did you try other model selection methods rather than stepwise ?
 
#4
You do not need to worry that the intercept beta0 hat is insignificant. What you need to consider seriously is the regression coefficients of each predictor variables. They must all pass the significance test. As to the intercept term, just leave it.
 

TheEcologist

Global Moderator
#5
You do not need to worry that the intercept beta0 hat is insignificant. What you need to consider seriously is the regression coefficients of each predictor variables. They must all pass the significance test. As to the intercept term, just leave it.
Depends on what you want to know.

In some cases people are actually interested in the intercept. e.g. base performance in absence of variable x (x=0) or height of different species of offspring at birth ect ect....

In that case it certainly matters, but in 90% in the cases it isn't important as 'a little boy' states; people are mostly interested linear relationship between variables. So you need to ask yourself what do you want to know and how does the intercept fit in.
 
#6
Depends on what you want to know.

In some cases people are actually interested in the intercept. e.g. base performance in absence of variable x (x=0) or height of different species of offspring at birth ect ect....

In that case it certainly matters, but in 90% in the cases it isn't important as 'a little boy' states; people are mostly interested linear relationship between variables. So you need to ask yourself what do you want to know and how does the intercept fit in.
Thank you TheEcologist, I learned a lot! :tup: