Tom Backer Johnsen wrote:
Greg Snow wrote:
No problem, adjusted R-squared can be negative. If there truly is no
relationship, then the adjusted R-squared should average to 0, so
sometimes it must be negative. All of your R-squared and adjusted
R-squared values suggest that there is not much
] in R when I get negative adjusted R^2 using lm, what
might be the problem?
This is a linear regression of Y onto factors...
If I take log of Y, and regress onto the factors, I got:
Multiple R-squared: 0.4023, Adjusted R-squared: 0.2731
If I don't take log of Y, and directly regress Y
Greg Snow wrote:
No problem, adjusted R-squared can be negative. If there truly is no
relationship, then the adjusted R-squared should average to 0, so sometimes it
must be negative. All of your R-squared and adjusted R-squared values suggest
that there is not much of a relationship (less
This is a linear regression of Y onto factors...
If I take log of Y, and regress onto the factors, I got:
Multiple R-squared: 0.4023, Adjusted R-squared: 0.2731
If I don't take log of Y, and directly regress Y onto the factors, I got:
Multiple R-squared: 0.1807, Adjusted R-squared:
And in the non-log case, all the previously significant coefficients
now became insignificant...
On Sun, Nov 9, 2008 at 5:36 PM, Michael [EMAIL PROTECTED] wrote:
This is a linear regression of Y onto factors...
If I take log of Y, and regress onto the factors, I got:
Multiple R-squared:
5 matches
Mail list logo
