# Normalization of 'change variables' in logistic regression [duplicate]

I am running a logit model trying to predict purchases on a dataset including change variables, i.e. I have a dataset of this kind:

              webvisits.month1  webvisits.month2 webvisits.month3 Purchase
contract1          34                   21            22          0
contract2          11                   2             2           1
contract3          9                    22            17          1
contractn          5                    44            42          0


The model is not performing well at all, would it be a good idea to try and normalize my variables? Would that affect the outcome? If this is the case, should I normalize them by month (considering the values by variable webvisits.month1, webvisits.month2 and so on) or rather by contract (e.g. considering the distribution contract1 [34,21,22,0], contract2 [11,2,2,1] and so on? Thanks, hope this makes sense.

• What do you mean with "normalize"? There are many different techniques that could be called that. Regardless, I would expect none of them to really help. – Maarten Buis Sep 29 '16 at 13:15
• I think you will find the information you need in the linked thread. Please read it. If it isn't what you want / you still have a question afterwards, come back here & edit your question to state what you learned & what you still need to know. Then we can provide the information you need without just duplicating material elsewhere that already didn't help you. – gung - Reinstate Monica Sep 29 '16 at 14:24
• Thank you, differently from the thread you're referring to, I was asking about normalization in logistic regression and whether the normalization is more appropriate across variables or across observations. – La Machine Infernale Sep 29 '16 at 18:28
• @LaMachineInfernale, you need to ping me (as at the beginning of this comment), or I won't be notified that you said something. What do you mean by "normalized" here, scaled to lie between 0 & 1? If you can clarify what you're asking, your question may not be a duplicate & may be a good one here. If so, I can re-open this. – gung - Reinstate Monica Sep 30 '16 at 0:58