Re: Multicollinearity Problem in Moderation Model

Posted by Bruce Weaver on Apr 02, 2013; 2:09pm
URL: http://spssx-discussion.165.s1.nabble.com/Multicollinearity-Problem-in-Moderation-Model-tp5719225p5719233.html

Frans addressed the first part of your question.  I'll take a stab at the second part.  Showing a significant effect in one group but not in the other is not the same thing as showing a significant interaction.  The two approaches are asking different questions.  For some simple examples, see this note by Kevin Thorpe:

   http://www.angelfire.com/wv/bwhomedir/notes/thorpe_ci_examples.pdf

HTH.

E. Bernardo wrote

Dear Experts,

Our moderation model has four continuous independent variables(IVs), only one dichotomous moderator variable(Mo) and continuous dependent.  All variables are not latent, so we tried to use linear regression model with the product terms of IV and Mo serve as the moderating variable. We used centered IVs. We've examined the multicollinearity statistics and found out that some have tolerance of 0 to .03 and VIF of 5 and above.  Our sample size is just n=218.  Results of the regression analysis (the moderation model above) show that there is no significant moderation effect.

On the other hand, we tried to do two separate regression analysis: one model for each group of the moderating variable ( with n1= 100, n2=118).  Results show that two of the IVs in one group are significant (p<.01), while all of the IVs in the other group are nonsignificant (p>.05).  Do these results indicate significant moderation effect?

Please advise how can we address the multicollinearity problem?

Thank you.
Eins