1
$\begingroup$

I have 4 models in the hierarchical regression output. The models are as follows: Model 1: Control variable Model 2: Control variable and 11 independent variables. Model 3: Control variable, 11 independent variables and moderator. Model 4: Control variable, 11 independent variables, moderator and interaction terms.

My question is this:

Which of the 4 models do I consider for final output interpretation? Whether there is a significant relation between different predictors and the outcome variable changes from model to model, in that the relationships that are significant in Model 1 become insignificant in subsequent models.

$\endgroup$
2
  • $\begingroup$ "Moderator" generally means an independent variable that interacts with another to affect the dependent variable. Therefore, if model 3 has a moderator, it needs an interaction term. I don't see why you would have a model 3 separate from your model 4. $\endgroup$
    – rolando2
    Jun 3, 2012 at 18:16
  • $\begingroup$ Thanks for your reply. I added the moderator separately in Model 3 because I wanted to see how it affects the outcome variable when introduced alone. Surprisingly, I found a significant relationship btw the moderator and the outcome variable, but no significant relation between the interaction terms and the outcome variable. I hope I'm doing it the right way. I just wanted to post the result here, but don't know how to do it, please leme know if I can. Thanks for your help:) $\endgroup$
    – Muzi
    Jun 3, 2012 at 19:27

1 Answer 1

1
$\begingroup$

Opinions vary on this, but my view is that you report the model that makes the most substantive sense; the one that advances knowledge the most, answers your research questions the best and so on.

Of course, that presupposes sufficient N to avoid overfitting the model.

You also may want to report all four models; from what you say, it seems like that would add the most information.

$\endgroup$
4
  • $\begingroup$ Thanks for your answer. Just wondering if I could post the result here to have your comments. Thanks:) $\endgroup$
    – Muzi
    Jun 3, 2012 at 19:28
  • $\begingroup$ Sure, why not? And other people may giver their comments too. $\endgroup$
    – Peter Flom
    Jun 3, 2012 at 20:26
  • $\begingroup$ Hi: Here is the link to the file containing the output ( mediafire.com/view/?208z1tw155e6juy ). The R square is quite high - is it "too good" for humanities research? Appreciate your views and thank you. $\endgroup$
    – Muzi
    Jun 3, 2012 at 21:03
  • $\begingroup$ I don't see any reason, offhand, that it's too high. Did you check for high leverage/influential points? Did you plot things? $\endgroup$
    – Peter Flom
    Jun 4, 2012 at 11:22

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.