BookmarkSubscribeRSS Feed
subhadip_kumar
Calcite | Level 5

if in a linear regression model p values are less than 0.05 and VIF is less than 2 what will be the correct answer. I'm confused with below the answers and don't know which one is correct?

 

collinearity is not a problem since all VI values are less than 10

collinearity is not a problem since all P values are less than 0.05.

2 REPLIES 2
PaigeMiller
Diamond | Level 26

collinearity is not a problem since all VI values are less than 10

 

A usual "rule of thumb" that I have heard is that VIF values should be less than 3. I have never heard 10, but maybe that's what some people think and I haven't read those articles. In any event, asking if "collinearity is not a problem" assumes we know what "problem" means, and that's not defined. Furthermore, collinearity has a big impact on some estimation methods, and less of an impact on other estimation methods, and you don't say what method you are using.

 

I would say that if you have real data that is not from a designed orthogonal experiment, then collinearity is present and you should examine its effect. I have never seen real data that is not from a designed orthogonal experiment that doesn't have collinearity, and you should be concerned.

 

You cannot determine the effect of collinearity by looking at p-values. In fact, collinearity works the other way, it can make the p-values questionable.

--
Paige Miller
Ksharp
Super User
Did you also try CORRB option in MODEL statement ?

I would pick up the first one .
How to Concatenate Values

Learn how use the CAT functions in SAS to join values from multiple variables into a single value.

Find more tutorials on the SAS Users YouTube channel.

SAS Training: Just a Click Away

 Ready to level-up your skills? Choose your own adventure.

Browse our catalog!

Discussion stats
  • 2 replies
  • 1137 views
  • 0 likes
  • 3 in conversation