James Salsman <[EMAIL PROTECTED]> writes: > I thought the point of adjusting the R^2 for degrees of > freedom is to allow comparisons about goodness of fit between > similar models with different numbers of data points. Someone > has suggested to me off-list that this might not be the case. > > Is an ADJUSTED R^2 for a four-parameter, five-point model > reliably comparable to the adjusted R^2 of a four-parameter, > 100-point model? If such values can't be reliably compared > with one another, then what is the reasoning behind adjusting > R^2 for degrees of freedom?
Well, the adjusted R^2 is the percent variance explained by covariates. So it compares the conditional variance (given covariates) to the marginal variance. This is less sensitive to DF issues than the usual R^2, but it does still require that both quantities make sense. This is not a given, and in particular the R^2 (either one) is quite dubious when the covariates are chosen by design. > What are the good published authorities on this topic? Dunno. Common sense should really suffice in this matter. -- 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 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
