Re: Regression or correlation

Posted by Ryan on Jan 01, 2010; 3:44pm
URL: http://spssx-discussion.165.s1.nabble.com/cronbach-alpha-for-binary-responses-tp1086058p1086068.html

Humphrey,

Since another poster has addressed why multiple regression (MR) is preferred over bivariate correlations, I will skip to how one can go about answering one of your research questions. Suppose you wanted to test if the coefficient of subscale 1 is significantly different than the coefficient of subscale 2. Assuming subscales 1 and 2 are on the same scale, one could run an MR analysis including the following predictors: (1) sum of subscales 1 and 2, (2) difference of subscales 1 and 2, and (3) subscale 3. If the coefficient of the difference variable is statistically significant, then you can conclude that the coefficients of the original subscale variables, 1 and 2, are significantly different. This approach was discussed in detail in another forum--let me know if you're interested and I can send the link.

There are several assumptions to running MR, including but not limited to normally distributed residuals, homoscedasticity and linearity. If you decide to run an MR analysis, I recommend that you review these assumptions among others, and of course, check for outliers and influential points. Much can be said on the necessary diagnostics to running MR. Write back if you have specific questions on assumptions etc.

Ryan

Humphrey-6 wrote

Dear folks,
I am studying the relationship between EQ and job success (JB). I also want to know which of the subscales of EQ is a better predictor of JB.
I think I should use multiple regression.
My colleague, however, says there is no need to take the trouble and complexities of regression. We can simply correlate each subscale of EQ with JB separately and compare the correlations. He believes that the subscale that has the highest correlation with JB will also turn out to be its best predictor in regression analysis. And that regression is an unnecessary and useless statistical development. There is nothing regression does that correlation cannot do!!! I cant think of anything to justify the superiority of regression over correlation here.
Can you please help me justify it?
Cheers
Humphrey