Multicollinearity in SPSS

Posted by Love-2 on Aug 01, 2006; 8:15pm
URL: http://spssx-discussion.165.s1.nabble.com/Multicollinearity-in-SPSS-tp1070043.html

Hi guys,

I just found about this forum today and I am really happy for that. I am writing a PhD thesis and could not get much help from my advisor so far.
I have a dataset with categories to run a logistic regression. However, i want to check for multicollinearity before I run the log. regression. A book on SPSS says  to run a linear regression and ignore the rest of the ouput but focus on the Coefficients table and the columns labelled collinearity Statistics. My questions are:

The correlation between two variables ( fathers’ Spanish origin and mother’s Spanish origin) is -0.714. Another warning sign, the Pearson correlation between these variables also suggests multicollinearity (Pearson correlation of 0.808). However I am not sure if tolerance value is small enough to raise concern (0.293) or the VIF is  higher than the cut-off point advisable for a logistic regression (3.416). Some researchers say the cut-off for the tolerance is 0.1 or 0.2 and the VIF is 4, but one book says "Values of VIF exceeding 10 are often regarded as indicating multicollinearity, but in weaker models, which is often the case in logistic regression, values above 2.5 may be a cause for concern"

So, what do you guys think? Should I drop one of the variables? I also have a similar case with mother's race and father's race, only a little less correlation (0.619)

Another question is: Although the book said to ignore the other outputs, I couldn't help and see that some of the  condition values are very high in the collinearity diagnostics table. Should I care at all about these values or should just look at the other statistics like tolerance and VIF and correlation values?

- Also, Is there any other way to check for multicolinearity in this type of dataset in SPSS?

Please reply to any questions you might know the answer!

Many thanks, Love.