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 of a relationship >> (less without the transform). > > Nevertheless, there remains the logical problem of a negative squared > value.
Not really, it is an adjusted squared value, not a squared adjusted one... Other programs have used "% variance accounted for", which is effectively the same thing modulo a factor of 100%, and that too can be negative if the variance actually increases. > > In any case, given the relatively large difference between the R-square > and the adjusted value, he probably has a relative large number of > independent variables compared to the number of rows in the data set. > And the dependent variable is probably quite skewed as well. Yes. An unfortunately placed large outlier could have this sort of effect. (Was the orignal question homework? If so, the intention was probably to have the student look into residuals and influence plots. If not, it still seem like that would be a good idea.) -- O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
