Calculating the Y' variable

Shachar

New Member
Hi everyone.

I wanted to see if my data could be described better with a non-linear relationship. So I calculated a new Y' variable, based on the coefficients I got from the regression model. Just to make sure I didn't make any mistakes, I rerun the regression, with only the new Y' as the predictor. The results were the same. Then, I used the curve fit option in SPSS to look for a better relationship

However, when I try to do the same thing with an interaction variable, this doesn't seem to work. The regression loses a lot of R^2.
Why is this and what can I do to make it work?

Thanks

obh

Active Member
Do you mean you use the same Y' but there is interactions in Y calculation? (first: Y=b+a2x1+a2x2+... via Y=b+a1x1+a12x1x2+a2x2))

Shachar

New Member
No. What I mean is that when I enter the interaction variables I recalculate Y' (Lets call it Y''), according to the new coefficients, and also include the interaction variable. However, while Y' explains all the variance in it's model, Y'' does not.

obh

Active Member
Hi Shachar

I think this is what I wrote above...
First: Y=b+a2x1+a2x2. =>new regression based only over estimate Y: ŷ => Y'=b'+a' ŷ high R
second: Y=b+a2x1+a2x2+a12x1x2 =>new regression based only over estimate Y: ŷ=> Y''=b''+a'' ŷ

If not please write an example as I did.

Shachar

New Member
Hi obh.

If I understood correctly then, yes, this is what I'm doing.

obh

Active Member
Hi Shachar,

I did a simple test and didn't get the same results as you described.
Can you please attach an excel file with the data you use?
Toda

Shachar

New Member
Hi obh. Sorry for the late reply.

Unfortunately, I can't upload the data. It's not something I can share.
Thank you for your effort!

obh

Active Member
No worry Shachar,

I feel that you may do a mistake, or I may misunderstand you.
So when you have some extra time you can try to create a simple example without revealing your real data 