Multiple regression with correlated variables

[#1]

Hi All,

I need some help with regards to multiple regression and would really appreciate any help! Thank you in advance :)

Here is a problem in a nutshell –

• I have continuous Y and 16 X’s
• When I run multivariate analysis, I can see some terms are correlated. Say, X1 and X2 are corelated, I can only use one of them
• Likewise, I have many such pairs
• However, I do want to arbitrarily pick X1 over X2. So, what I am doing right now is running the regression first with X1 and then with X2. Then, I compare the models with these terms. But the number of combinations I would need to run is simply too many, extremely time consuming while doing manually and prone to mistakes.
• Wanted to check if there is a smarter way of solving this.
• I know this can be solved with writing a script to run this in some kind of a loop and highlight the best models one the basis of –
  • R2, adj R2 value and
  • VIF
• However, do not have the knowledge to write scripts.
• Any other tips, tricks would also be great! (I do not have JMP Pro)

Look forward to hearing form you.

Best Regards,

Vipul

[#2]

Thank you so much @David_Burnham ! Very grateful for your feedback, it was very helpful. Much appreciated.

Best Regards,

Vipul

[#3]

FYI the procedure you describe for fitting one at a time over all X's is done automatically by the Response Screening platform found under Analyze> Screening.