Terias wrote:
Hello,
I was doing a linear regression with the following formula:
lm(y~x+0), so it passes through the origin. But when I called the summary of
the regression i saw that R squared is abnormally high (it's a lot lower in
other programs such as SigmaPlot and MS Excel).The manual explained the
cause of the difference (because of the different computing method), but
what should I do to get the same R^2 in excel and R?
If you insist, I think you can get what Excel does like this:
> x <- 1:10
> y <- rnorm(10)
## Residual sums of squares
> ss1 <- anova(lm(y~1))[1,2]
> ss2 <- anova(lm(y~x+0))[2,2]
## Relative reduction in sum of squares
> (ss1-ss2)/ss1
[1] -0.08576713
Now if you dislike the fact that R^2 can come out negative, that's your
problem....
WITHOUT PASSING THROUGH THE ORIGIN:
R^2: Multiple R-squared: 0.9711, Adjusted R-squared: 0.9654
In MS Excel: 0,9711
So it's OK.
WITH PASSING THROUGH THE ORIGIN:
Multiple R-squared: 0.9848, Adjusted R-squared: 0.9822
In MS Excel: 0,8907
So almost 10% difference.
Thank you for your help.
Csanad Bertok, Hungary
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c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
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~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907
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