Finding Correlations from an effect seen on the fit model

[#1]

I have a very large and complicated data set. When I run a fit model, I see an effect by one of my variables that are continuous. However, since I cannot run this through a bivariate analysis, I would like to try to run an analysis to see if the change in one variable is correlated to the change in the other value. How do I do this?

[#2]

I'm not sure I understand the situation. Are there two continuous variables you are looking to correlate?

"change in one variable is correlated to the change in the other value". What is the other value?

If the two variables are continuous, you can do Multivariate Analysis>Multivariate.  Put the two variables in the Y, columns box.  This will give you a scatter plot and default Pearson correlation coefficients.

If you are running Fit Model, Right click on the Parameter Estimates table in the output.  Select Columns>VIF.  This will give you variance inflation factor for all of the parameters.

[#3]

It sounds like you are looking for "interactions" between variables.  In the model, this would look like:

Y= b + B1*X1 + B2*X2 + X1*X2*B3 + e.   (the "B"'s are the parameters, or beta's, or... slopes)

In the fit model platform, you can "cross" one variable with others. An easy way to do this is to use the Macro button and choose Factorial to Degree. By default, this will give you all the two-way interactions.