Posted by
Jamie Burnett-3 on
Oct 22, 2006; 7:17pm
URL: http://spssx-discussion.165.s1.nabble.com/partial-vs-semi-partial-correlations-in-MR-tp1071617p1071619.html
I think they are both correct David, please note that Tabachnick talks about the unique contribution to the total variance of the DV, whilst Norusis says the unexplained variance in the DV.
Let's say you have a dependent variable Y and two independent variable X1 and X2, Partial correlations looks at the correlation between Y and X1 after accounting for the other IV X2 in both Y and X1, whilst semi-partial correlations show the correlation between Y and X1 after accounting for X2 in X1 only. This is why Tabachnick talks about total variance in Y when discussing semi-partial correlations and Norusis unexplained variance left in DV when discussing partial correlations.
Does this make sense?
I believe it is the square of the partial correlation that would be best to explain the unique contribution to the explained variance in DV.
Thanks
Jamie
________________________________
From: SPSSX(r) Discussion on behalf of David Wright
Sent: Sun 10/22/2006 4:24 PM
To:
[hidden email]
Subject: partial vs semi-partial correlations in MR
Just when I get this figured out I read more & get confused. Partial vs semi-partial correlations in multiple regsression-- which is the better measure squared to identify the unique contribution to the explained variance in the DV?
In Tabachnick & Fidell (2007, 5th ed, pp145-146) they note the "squared semi-partial correlations expresses the unique contribution of the IV to the total variance of the DV." Whereas Norusis (spss 14 statistical procedures companion, p248) states "The square of the partial correlation coefficient tells you waht proportion of the unexplained variance in the DV is explained..."
============================
This e-mail and all attachments it may contain is confidential and intended solely for the use of the individual to whom it is addressed. Any views or opinions presented are solely those of the author and do not necessarily represent those of Ipsos MORI and its associated companies. If you are not the intended recipient, be advised that you have received this e-mail in error and that any use, dissemination, printing, forwarding or copying of this e-mail is strictly prohibited. Please contact the sender if you have received this e-mail in error.
============================