wrong calculation of R-squared in summary.lm
This is user error: that fit has class c("mlm", "lm") and you should
be calling summary() on it, which will dispatch the mlm method.
For multiple-response linear models, there is also summary.manova.
On Wed, 30 Mar 2011, Stefan Schlager wrote:
Dear all, I just stumbled upon the fact, that when I perform a regression on multivariate responses, that are not centred, I get a ricilulously high R-squared value. After reading the code of summary.lm, I found a bug in the function summary.lm: mss is calculated by: mss <-sum((f - mean(f))^2) - where f are the fitted values. This works only for a single response variable, because otherwise the matrix containing the fitted values is scaled by a scalar. replacing this with: mss <- scale(f,scale=FALSE) solved the problem for me. Example for bug: response<-cbind(rnorm(500)+1000,rnorm(500)+300) predictor<-rnorm(500) fit<-lm(response ~ predictor) summary.lm(fit) now reports a R^2 value of 1!!! Please correct me, if I'm wrong Stefan Stefan Schlager M.A. Anthropologie Medizinische Fakult?t der der Albert Ludwigs- Universit?t Freiburg Hebelstr. 29 79104 Freiburg Anthropology Faculty of Medicine, Albert-Ludwigs-University Freiburg Hebelstr. 29 D- 79104 Freiburg phone +49 (0)761 203-5522 fax +49 (0)761 203-6898 On 30/03/11 13:54, r-help-request at r-project.org wrote:
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