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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.
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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
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I would pick up the first one .